UPLC-Q-TOF-MS/MS combined with machine learning methods for screening quality indicators of Hypericum perforatum L.

Hypericum perforatum L. (HPL), also known as St. John's wort, is one of the extensively researched domestically and internationally as a medicinal plant.

Network pharmacology and experimental verification study on the mechanism of Hedyotis diffusa Willd in treating colorectal cancer.

This study aimed to evaluate the pharmacological mechanism of Hedyotis diffusa Willd against CRC (colorectal cancer) using network pharmacological analysis combined with experimental validation. The active components and potential targets of Hedyotis diffusa Willd were screened from the tax compliance management program public database using network pharmacology. The core anti-CRC targets were screened using a protein-protein interaction (PPI) network.

Prediction of temperature distribution in a furnace using the incremental deep extreme learning machine.

In this article, a data-driven model based on the incremental deep extreme learning machine (IDELM) algorithm is proposed to predict the temperature distribution in the furnace. To this end, computational fluid dynamics (CFD) simulations are carried out first to get temperature distributions under typical working conditions. Based on the air distribution mode, the simulation results are divided into six subclasses.

Deep Learning Models for SO Distribution in a 30 MW Boiler via Computational Fluid Dynamics Simulation Data.

The distribution of SO in a boiler is an important factor affecting tube corrosion in a furnace. To investigate the correlation between SO distribution and numerous variables (e.g.