AIMC Topic: Microplastics

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Behavioral toxicological tracking analysis of Drosophila larvae exposed to polystyrene microplastics based on machine learning.

Journal of environmental management
Microplastics, as a pivotal concern within plastic pollution, have sparked widespread apprehension due to their ubiquitous presence. Recent research indicates that these minuscule plastic particles may exert discernible effects on the locomotor capab...

Application of machine learning and multivariate approaches for assessing microplastic pollution and its associated risks in the urban outdoor environment of Bangladesh.

Journal of hazardous materials
Microplastics (MPs) are an emerging global concern due to severe toxicological risks for ecosystems and public health. Therefore, this is the first study in Bangladesh to assess MP pollution and its associated risks for ecosystems and human health in...

The adsorption and release mechanism of different aged microplastics toward Hg(II) via batch experiment and the deep learning method.

Chemosphere
Aged microplastics are ubiquitous in the aquatic environment, which inevitably accumulate metals, and then alter their migration. Whereas, the synergistic behavior and effect of microplastics and Hg(II) were rarely reported. In this context, the adso...

First Record of Microplastic Contamination in the Non-Native Dark False Mussel (Bivalvia: Dreissenidae) in a Coastal Urban Lagoon.

International journal of environmental research and public health
Microplastic contamination is a global concern due to its conspicuous presence in aquatic ecosystems and its toxic nature to environmental and human health. False mussels are among the most notable fresh- and brackish water invaders. The invasive in...

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.

Journal of hazardous materials
Microplastics (MPs) and nanoplastics (NPs) are global pollutants with emerging concerns. Methods to predict and screen their toxicity are crucial. Elemental dyshomeostasis can be used to assess toxicity of environmental pollutants. Non-targeted metal...

Automatic classification of microplastics and natural organic matter mixtures using a deep learning model.

Water research
Several preprocessing procedures are required for the classification of microplastics (MPs) in aquatic systems using spectroscopic analysis. Procedures such as oxidation, which are employed to remove natural organic matter (NOM) from MPs, can be time...

Leveraging deep learning for automatic recognition of microplastics (MPs) via focal plane array (FPA) micro-FT-IR imaging.

Environmental pollution (Barking, Essex : 1987)
The fast and accurate identification of MPs in environmental samples is essential for the understanding of the fate and transport of MPs in ecosystems. The recognition of MPs in environmental samples by spectral classification using conventional libr...

Prediction of microplastic abundance in surface water of the ocean and influencing factors based on ensemble learning.

Environmental pollution (Barking, Essex : 1987)
Microplastics are regarded as emergent contaminants posing a serious threat to the marine ecosystem. It is time-consuming and labor-intensive to determine the number of microplastics in different seas using traditional sampling and detection methods....

Spectral Classification of Large-Scale Blended (Micro)Plastics Using FT-IR Raw Spectra and Image-Based Machine Learning.

Environmental science & technology
Microplastics (MPs) are currently recognized as emerging pollutants; their identification and classification are therefore essential during their monitoring and management. In contrast to most studies based on small datasets and library searches, thi...

A Critical Review on Artificial Intelligence-Based Microplastics Imaging Technology: Recent Advances, Hot-Spots and Challenges.

International journal of environmental research and public health
Due to the rapid artificial intelligence technology progress and innovation in various fields, this research aims to use science mapping tools to comprehensively and objectively analyze recent advances, hot-spots, and challenges in artificial intelli...