AIMC Topic: Aerosols

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Virtual Impactor-Based Label-Free Pollen Detection using Holography and Deep Learning.

ACS sensors Nov 22, 2022
Exposure to bio-aerosols such as pollen can lead to adverse health effects. There is a need for a portable and cost-effective device for long-term monitoring and quantification of various types of pollen. To address this need, we present a mobile and...
Aerosols Holography Pollen Deep Learning Particulate Matter
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Validation, analysis, and comparison of MISR V23 aerosol optical depth products with MODIS and AERONET observations.

The Science of the total environment Sep 29, 2022
The latest Multi-angle Imaging Spectro Radiometer (MISR) Version (V) 23 aerosol optical depth (AOD) products were released, with an improved spatial resolution of 4.4 km, providing an unprecedented opportunity for the refined regional application. To...
Reproducibility of Results Robotics Forests Humans Aerosols
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Dynamic Imaging and Characterization of Volatile Aerosols in E-Cigarette Emissions Using Deep Learning-Based Holographic Microscopy.

ACS sensors Jun 3, 2021
Various volatile aerosols have been associated with adverse health effects; however, characterization of these aerosols is challenging due to their dynamic nature. Here, we present a method that directly measures the volatility of particulate matter ...
Propylene Glycol Deep Learning Microscopy Aerosols Electronic Nicotine Delivery Systems
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Understanding global changes in fine-mode aerosols during 2008-2017 using statistical methods and deep learning approach.

Environment international Jan 29, 2021
Despite their extremely small size, fine-mode aerosols have significant impacts on the environment, climate, and human health. However, current understandings of global changes in fine-mode aerosols are limited. In this study, we employed newly devel...
Humans Deep Learning China Seasons Aerosols Mexico Australia India Air Pollutants Environmental Monitoring
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New interpretable deep learning model to monitor real-time PM concentrations from satellite data.

Environment international Sep 10, 2020
Particulate matter with a mass concentration of particles with a diameter less than 2.5 μm (PM) is a key air quality parameter. A real-time knowledge of PM is highly valuable for lowering the risk of detrimental impacts on human health. To achieve th...
Environmental Monitoring Air Pollutants Air Pollution China Cities Particulate Matter Beijing Aerosols Humans Deep Learning
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Raman spectroscopy of potential bio-hazards commonly found in bio-aerosols.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jul 31, 2020
Pathogenic bio-aerosols are a threat to public health today, and thus quick detection and identification is of paramount importance. In this study, Raman spectroscopy was used to test 14 types of pollens, one type of fungus and two types of bacteria ...
Spectrum Analysis, Raman Support Vector Machine Principal Component Analysis Aerosols Bacteria
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Heavy metals in submicronic particulate matter (PM) from a Chinese metropolitan city predicted by machine learning models.

Chemosphere Jul 8, 2020
The aim of this study was to establish a method for predicting heavy metal concentrations in PM (aerosol particles with an aerodynamic diameter ≤ 1.0 μm) based on back propagation artificial neural network (BP-ANN) and support vector machine (SVM) me...
Metals, Heavy Meteorological Concepts Betacoronavirus Pneumonia, Viral Coronavirus Infections Seasons Aerosols Particulate Matter Environmental Exposure Humans Neural Networks, Computer China Cities Environmental Monitoring Support Vector Machine Air Pollutants Computer Simulation Air Pollution Pandemics Wind SARS-CoV-2 COVID-19
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Fast Pathogen Identification Using Single-Cell Matrix-Assisted Laser Desorption/Ionization-Aerosol Time-of-Flight Mass Spectrometry Data and Deep Learning Methods.

Analytical chemistry May 11, 2020
In diagnostics of infectious diseases, matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) can be applied for the identification of pathogenic microorganisms. However, to achieve a trustworthy identification fr...
Gram-Positive Bacteria Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Deep Learning Aerosols Gram-Negative Bacteria Single-Cell Analysis
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Forecasting of bioaerosol concentration by a Back Propagation neural network model.

The Science of the total environment Sep 5, 2019
Bioaerosol in the atmosphere plays a very important role in environment and public health. To forecast the bioaerosol concentration, the correlation between bioaerosol concentration and meteorological factors was discussed, and a Back Propagation (BP...
Neural Networks, Computer Environmental Monitoring Meteorological Concepts Air Pollution Aerosols Atmosphere
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Correlating exhaled aerosol images to small airway obstructive diseases: A study with dynamic mode decomposition and machine learning.

PloS one Jan 31, 2019
BACKGROUND: Exhaled aerosols from lungs have unique patterns, and their variation can be correlated to the underlying lung structure and associated abnormities. However, it is challenging to characterize such aerosol patterns and differentiate their ...
Lung Diseases, Obstructive Male Middle Aged Breath Tests Image Processing, Computer-Assisted Support Vector Machine Exhalation Algorithms Principal Component Analysis Humans Prognosis Aerosols Machine Learning Tomography, X-Ray Computed
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