Environmental Health

An Efficient Group Federated Learning Framework for Large-Scale EEG-Based Driver Drowsiness Detection.

To avoid traffic accidents, monitoring the driver's electroencephalogram (EEG) signals to assess drowsiness is an effective solution. However, aggregating the personal data of these drivers may lead to insufficient data usage and pose a risk of privacy breaches. To address these issues, a framework called Group Federated Learning (Group-FL) for large-scale driver drowsiness detection is proposed, ...

Analysis of land use and land cover change using machine learning algorithm in Yola North Local Government Area of Adamawa State, Nigeria.

The dynamic use of land that results from urbanization has an impact on the urban ecosystem. Yola North Local Government Area (Yola North LGA) of Adamawa state, Nigeria, has experienced tremendous changes in its land use and land cover (LULC) over the past two decades due to the influx of people from rural areas seeking for the benefits of its economic activities. The goal of this research is to d...

Optimization of laccase from Stenotrophomonas maltophilia E1 by submerge fermentation using coconut husk with its detoxification and biodecolorization ability of synthetic dyes.

Enzymatic degradation of synthetic dyes holds an immense promise for addressing the environmental concerns associated with the textile and dye industr...

Atmospheric elemental carbon pollution and its regional health disparities in China.

Previous studies have reported that atmospheric elemental carbon (EC) may pose potentially elevated toxicity when compared to total ambient fine parti...

Semi-Supervised Learning for Low-Cost Personalized Obstructive Sleep Apnea Detection Using Unsupervised Deep Learning and Single-Lead Electrocardiogram.

OBJECTIVE: Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder that can lead to a wide range of health issues if left untreated...

Different electrolytic treatments for food sanitation and conservation simulating a wash process at the packinghouse.

UNLABELLED: Microorganisms are predominantly responsible for food deterioration, necessitating the sanitization and removal of these entities from foo...

Screening the phytotoxicity of micro/nanoplastics through non-targeted metallomics with synchrotron radiation X-ray fluorescence and deep learning: Taking micro/nano polyethylene terephthalate as an example.

Microplastics (MPs) and nanoplastics (NPs) are global pollutants with emerging concerns. Methods to predict and screen their toxicity are crucial. Ele...

Assessing evidence on the impacts of nature-based interventions for climate change mitigation: a systematic map of primary and secondary research from subtropical and tropical terrestrial regions.

BACKGROUND: Nature-based interventions (NbIs) for climate change mitigation include a diverse set of interventions aimed at conserving, restoring, and...

Combination of headspace single-drop microextraction (HS-SDME) with a nickel-embedded paper-based analytical device for cyanide quantification.

BACKGROUND: Cyanide anion can be found in foodstuffs, tobacco smoke and a variety of types of waters, mainly originating from anthropogenic activities...

TFEB/LAMP2 contributes to PM-induced autophagy-lysosome dysfunction and alpha-synuclein dysregulation in astrocytes.

Atmospheric particulate matter (PM) exacerbates the risk factor for Alzheimer's and Parkinson's diseases (PD) by promoting the alpha-synuclein (α-syn)...

Predicting Antioxidant Synergism via Artificial Intelligence and Benchtop Data.

Lipid oxidation is a major issue affecting products containing unsaturated fatty acids as ingredients or components, leading to the formation of low m...

Spatio-temporal fusion of meteorological factors for multi-site PM2.5 prediction: A deep learning and time-variant graph approach.

In the field of environmental science, traditional methods for predicting PM2.5 concentrations primarily focus on singular temporal or spatial dimensi...

An integrated modelling framework for multiple pollution source identification in surface water.

Pollution source identification is vital in water safety management. An integrated simulation-optimization modelling framework comprising a process-ba...

The role of intelligent technology in the development of urban air mobility systems: A technical perspective.

Urban Air Mobility (UAM) is an emerging transportation system that aims at revolutionizing urban mobility through the deployment of small electric ver...

Chemical profiling of principle active and toxic constituents in herbs containing aristolochic acids.

OBJECTIVE: To clear the amounts of the principal active/toxic components in herbs containing aristolochic acids (HCAAs), which are still used as medic...

Deep Learning Neural Network-Guided Detection of Asbestos Bodies in Bronchoalveolar Lavage Samples.

INTRODUCTION: Asbestos is a global occupational health hazard, and exposure to it by inhalation predisposes to interstitial as well as malignant pulmo...

Cheminformatics and Machine Learning Approaches to Assess Aquatic Toxicity Profiles of Fullerene Derivatives.

Fullerene derivatives (FDs) are widely used in nanomaterials production, the pharmaceutical industry and biomedicine. In the present study, we focused...

Comparison of post reconstruction- and reconstruction-based deep learning denoising methods in cardiac SPECT.

. The quality of myocardial perfusion SPECT (MPS) images is often hampered by low count statistics. Poor image quality might hinder reporting the stud...

Investigation of spatiotemporal distribution and formation mechanisms of ozone pollution in eastern Chinese cities applying convolutional neural network.

Severe ground-level ozone (O) pollution over major Chinese cities has become one of the most challenging problems, which have deleterious effects on h...

Application of classification machine learning algorithms for characterizing nutrient transport in a clay plain agricultural watershed.

Excess nutrients in surface water and groundwater can lead to water quality deterioration in available water resources. Thus, the classification of nu...