Search

The pupose of this review was to explore the application of machine learning in the realm of flavor molecule research, particularly in the analysis of the flavor of Jasmine tea. The study of flavor molecules is fundamental to understand and optimize the taste and quality of food, especially tea. The introduction of machine learning technology has opened new horizons for the identification and analysis of flavor molecules. This paper firstly outlined the basic concepts and research methods of flavor molecules, and a detailed discussion on the application of machine learning in deciphering the relationships between molecular structures and flavor characteristics, as well as in the analysis, prediction and optimization of the flavor and intelligent processing of Jasmine tea and other applications, put forward the research prospect. Thereby, this review could enhance the quality of Jasmine tea and provide technical support for the further development of the tea industry.

With the evolution of war forms and development of weapon equipment systems, the new intelligent equipment selection and decision-making methods are more and more important for equipment construction top-level planning and combat decision making. Based on the systematic analysis of the background and development status of equipment combination selection, this paper explains the conceptual connotation and technical framework of equipment combination selection, discusses the main methods of equipment combination selection from four aspects: problem construction, candidate equipment space construction, value construction and optimization selection, and analyzes the existing problems and development trend, and provides reference for the research and application of equipment combination selection.

In this article, Fe–8.5Mn–1.5Al medium‐manganese steel is taken as the research object, and Gleeble 3500 thermal simulation testing machine is used to conduct isothermal compression at different deformation temperatures, strain rates, and strains in its austenite ferrite two‐phase zone. A constitutive model and a dynamic recrystallization volume fraction model for materials are established, and finite‐element method is used to simulate the temperature, equivalent strain, and dynamic recrystallization volume fraction distribution in different regions of the workpiece under different deformation conditions. By comparing and analyzing the microstructure, finite‐element simulation results, and hot working diagrams obtained from the experiment, the microscopic mechanism of dynamic softening of the material when ferrite and austenite coexist is explained; the transformation of the dynamic softening mechanism of the two phases with the hot deformation process is also explained. Early deformation mainly occurs in softer ferrite, which preferentially undergoes continuous dynamic recrystallization. Austenite has a lower stacking fault energy, and discontinuous dynamic recrystallization (DDRX) occurs when the dislocation density reaches a certain critical value. At the same time, when the strain reaches a certain level, the dynamic softening behavior of ferrite will also transform into DDRX. The optimal deformation conditions for Fe–8.5Mn–1.5Al medium‐manganese steel during warm processing in the two‐phase zone are a temperature of 720 °C, a strain rate of 0.01 s−1, and a large deformation zone. [ABSTRACT FROM AUTHOR]

Objective To explore the role of calcium release activated calcium channel protein 1 (Orai1) in bone marrow mesenchymal stem cells (BMSCs) osteogenesis induced by bone morphogenetic protein 9 (BMP9). Methods BMSCs were isolated by adherent method, and the third generation BMSCs were treated with 10－5mol/L of BMP9, and the mRNA expression of Orai1 was measured at different time points. RT-qPCR and Western blot were used to value the transfection efficiency after Orai1 knockdown. The osteogenic markers of Runx2, OPN and OCN were detected by RT-qPCR. Hydroxyapatite/PLA/chitosan, a scaffold material for bone tissue engineering, was implanted into the subcutaneous of nude mice. After 4 weeks, the osteogenic effect was examined by microscopy. Results The mRNA expression of Orai1 increased gradually at the 5th day after BMP9 induction (P＜0.05). The gene and protein expression of Orai1 decreased significantly after Orai1 knockdown (P＜0.05). Besides, the osteogenic effect of Orai1 knockdown decreased significantly, and the expression of Runx2, OPN and OCN gene decreased significantly (P＜0.05). Moreover, BMP9 could significantly improve the ectopic osteogenic ability of BMSCs, and Orai1 knockdown significantly inhibited this effect (P＜0.05). Conclusions BMP9 plays an important role in osteogenic differentiation of BMSCs potentially by regulating Orai1.