AIMC Topic: Volatile Organic Compounds

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Distribution characteristics of volatile organic compounds and its multidimensional impact on ozone formation in arid regions based on machine learning algorithms.

Environmental pollution (Barking, Essex : 1987)
Volatile Organic Compounds (VOCs) are key components of atmospheric pollution and play a critical role in ozone (O) formation. Understanding their distribution and pollution sources is essential to grasping the multifaceted impact of VOCs on O produc...

Overcoming methodological barriers in electronic nose clinical studies, a simulation data-based approach.

Journal of breath research
Analysis of volatile organic compounds by electronic nose (e-nose) may address gaps in non-invasive screening for neoplasia. Machine learning impacts study design and sample size requirements, but guidance on clinical study design is limited. This st...

Identification of Different Steaming Degrees of Panax quinquefolius L. Based on GC-IMS Combined With Machine Learning.

Rapid communications in mass spectrometry : RCM
RATIONALE: Panax quinquefolius L. (PQ), a commonly used traditional Chinese medicine and a food, is usually processed into various products, including white PQ, red PQ (two- or three-time steamed PQ), and black PQ (nine-time steamed PQ). Previous stu...

The impact of multipollutant exposure on hepatic steatosis: a machine learning-based investigation into multipollutant synergistic effects.

Frontiers in public health
INTRODUCTION: This study examines the synergistic effects of multi-pollutant exposure on hepatic lipid accumulation in non-alcoholic fatty liver disease (NAFLD) through the application of an explainable machine learning framework. This approach addre...

Enhancing beer authentication, quality, and control assessment using non-invasive spectroscopy through bottle and machine learning modeling.

Journal of food science
Fraud in alcoholic beverages through counterfeiting and adulteration is rising, significantly impacting companies economically. This study aimed to develop a method using near-infrared (NIR) spectroscopy (1596-2396 nm) through the bottle, along with ...

Estimating exposures from spray products using robotic simulations.

Annals of work exposures and health
There is an increasing need for exposure data to enable more precise information for risk estimates and improved public health protection. While personal monitoring data are preferred, it is often difficult to collect due to the resources needed to c...

Automated Gas Chromatography Peak Alignment: A Deep Learning Approach using Greedy Optimization and Simulation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The clinical significance of volatile organic compounds (VOC) in detecting diseases has been established over the past decades. Gas chromatography (GC) devices enable the measurement of these VOCs. Chromatographic peak alignment is one of the importa...

A new multi-scale backbone network for object detection based on asymmetric convolutions.

Science progress
Real-time object detection on mobile platforms is a crucial but challenging computer vision task. However, it is widely recognized that although the lightweight object detectors have a high detection speed, the detection accuracy is relatively low. I...

Parsing Sage and Rosemary in Time: The Machine Learning Race to Crack Olfactory Perception.

Chemical senses
Color and pitch perception are largely understandable from characteristics of physical stimuli: the wavelengths of light and sound waves, respectively. By contrast, understanding olfactory percepts from odorous stimuli (volatile molecules) is much mo...

A System-Wide Understanding of the Human Olfactory Percept Chemical Space.

Chemical senses
The fundamental units of olfactory perception are discrete 3D structures of volatile chemicals that each interact with specific subsets of a very large family of hundreds of odorant receptor proteins, in turn activating complex neural circuitry and p...