How does the novel model achieve accurate prediction of soybean futures prices?
Peer-Reviewed Publication
Updates every hour. Last Updated: 15-Jul-2025 20:11 ET (16-Jul-2025 00:11 GMT/UTC)
A study led by Professor Hui Liu from Central South University, published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2024599), introduces a hybrid deep learning model named “ICEEMDAN-LZC-BVMD-SSA-DELM”, which significantly enhances the prediction accuracy of soybean futures prices. By integrating multi-stage data preprocessing and intelligent optimization algorithms, the model addresses limitations of traditional methods in noise handling, parameter tuning, and generalization capabilities, offering new insights for risk management in agricultural financial markets.
Recently, the team led by Academician Wei-Hong Zhu at East China University of Science and Technology proposed a novel photo-rearrangement reaction of diarylethenes induced by intramolecular proton transfer (IPT), while exploring the reactivity of active carbon sites in diarylethene systems. In this study, published in CCS Chemistry, aldehyde and carboxyl groups were innovatively introduced at the active carbon positions, revealing distinct photoresponsive behaviors. The dialdehyde-substituted system exhibited typical reversible photochromism, whereas the dicarboxylate-substituted counterpart underwent an unexpected photorearrangement to yield polycyclic aromatic structures. Mechanistic studies, including transient absorption spectroscopy and density functional theory (DFT) calculations, demonstrated that the rearrangement proceeds through electrocyclization followed by an IPT-driven decarboxylation process. This work opens a new pathway for light-induced synthesis of polycyclic aromatic hydrocarbons and highlights potential applications in molecular modification, photoreaction mechanisms, and synthetic photochemistry.
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Cr-Nb containing refractory high-entropy alloys (RHEAs) excel in high strength beyond 1200℃ but a low density close to Ti-based alloys, which endow them promising for applications in aero engines. However, oxidation is the bottleneck that limits their practical applications. Recently, CrNbO4 has been found to effectively protect them from oxidation. Nevertheless, little is known about this oxide. To elucidate the protection mechanism of CrNbO4 and explore its properties, we report herein for the first time the microstructure, mechanical, and thermal properties of CrNbO4.
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