Publications by authors named "Huanqi Yang"

With rising consumer awareness of health and wellness, the demand for enhanced food safety is rapidly increasing. The generation of chemical contaminants during the thermal processing of food materials, including polycyclic aromatic hydrocarbons, heterocyclic aromatic amines, and acrylamide happens every day in every kitchen all around the world. Unlike extraneous chemical contaminants (e.

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Tartaric acid (TA) is a major non-fermentable plant soluble acid that abundantly occur in grapes and wines, imparting low pH and tart flavour to berries thereby regulating numerous quality attributes of wine, such as flavour, microbial stability, and aging potential. Evaluation of acidity in mature fruits of 21 wine grape (Vitis vinifera) varieties revealed significant variation between 'Beichun' and 'Gewürztraminer', which was correlated with TA content. RNA-seq analysis of fruits from the two cultivars at different developmental stages revealed that a transketolase gene, VvTK2, was significantly dominantly expressed in the high TA phenotype 'Beichun' variety.

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Food preservation is a critical issue in ensuring food safety and quality. Growing concern around industrial pollution of food and demand for environmentally sustainable food has led to increased interest in developing effective and eco-friendly preservation techniques. Gaseous ClO has gained attention for its strong oxidizing properties, high efficacy in microorganism inactivation, and potential for preserving the attributes and nutritional quality of fresh food while avoiding the formation of toxic byproducts or unacceptable levels of residues.

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Article Synopsis
  • - ECG classification is crucial for monitoring heart health, transitioning from traditional machine learning methods like SVM and KNN to advanced end-to-end neural networks, which offer better accuracy but are computationally heavy.
  • - The new study introduces an ultra-lightweight ECG classification neural network with significantly reduced computational complexity, making it suitable for low-cost microcontrollers while maintaining high accuracy (99.1%) in classification.
  • - Implemented on the MSP432 microcontroller, this innovative design consumes minimal power (0.4 mJ for normal and 3.1 mJ for abnormal heartbeats), enabling efficient real-time ECG monitoring without the drawbacks of existing hardware solutions.
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