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Identification of odor compounds in fresh sea buckthorn juice (FSBJ) and pulp (SBP) was performed by gas chromatography-mass spectrometry-olfactometry (GC-MS-O). A total of 39 and 36 odor compounds were identified in FSBJ and SBP, respectively. Further findings revealed that ethyl hexanoate, ethyl 2-methylbutyrate, ethyl 3-methylbutyrate, and 3-methylbutyl 3-methylbutanoate had high flavor dilution (FD) factors and were identified as the key odor compounds in FSBJ. In addition, the contents of ester compounds contributing to the fruity odor were significantly reduced in SBP after pasteurization. Sensory evaluation and electronic tongue analysis revealed that the sweetness and overall taste of SBP were superior to those of FSBJ. The contents of vitamin C and total flavonoids were significantly lower in SBP than in FSBJ, indicating that pasteurization reduces the nutritional quality of FSBJ. The results of the study can provide theoretical references for the flavor and nutritional quality optimization of sea buckthorn products.

Arginine vasopressin (AVP) is a key contributor to heart failure (HF), but the underlying mechanisms remain unclear. In the present study, a mouse model of HF and human cardiomyocyte (HCM) cells treated with dDAVP are generated in vivo and in vitro, respectively. Hematoxylin and eosin (HE) staining is used to evaluate the morphological changes in the myocardial tissues. A colorimetric method is used to measure the iron concentration, Fe2+ concentration and malondialdehyde (MDA) level. Western blot analysis is used to examine the protein levels of the V1a receptor (V1aR), calcineurin (CaN), nuclear factor of activated T cells isoform C3 (NFATC3), glutathione peroxidase 4 (GPX4) and acyl-CoA synthase long chain family member 4 (ACSL4). Immunoprecipitation (IP) and luciferase reporter assays are performed to determine the interaction between NFATC3 and ACSL4. Both in vivo and in vitro experiments reveal that the V1aR-CaN-NFATC3 signaling pathway and ferroptosis are upregulated in HFs, which are verified by the elevated protein levels of V1aR, CaN, NFATC3 and ACSL4; reduced GPX4 protein level; and enhanced Fe2+ and MDA levels. We further find that inhibiting NFATC3 by suppressing the V1aR/CaN/NFATC3 pathway via V1aR/CaN inhibitors or sh-NFATC3 not only alleviates HF but also inhibits AVP-induced ferroptosis. Mechanistically, sh-NFATC3 significantly reverses the increase in AVP-induced ACSL4 protein level, Fe2+ concentration, and MDA level by directly interacting with ACSL4. Our results demonstrate that AVP enhances ACSL4 expression by activating the V1aR/CaN/NFATC3 pathway to induce ferroptosis, thus contributing to HF. This study may lead to the proposal of a novel therapeutic strategy for HF.

The nuclear criticality safety issue in spent fuel reprocessing facilities is closely related to the main process and is almost equally important. It is closely related to the design and operation of reprocessing facilities. The requirement of nuclear criticality safety greatly restricts the operational capacity of the spent fuel reprocessing process, thereby affecting the economic efficiency of reprocessing. In the post-processing process, both multiphase uranium-plutonium mixed systems and multi body interaction systems are involved. The system characteristics are complex, and experimental simulation is difficult, which greatly restricts the further improvement of the production and operation capabilities of the pilot plant. However, due to the criticality safety challenges caused by reactivity changes such as the non-uniformity, dynamic complexity, and instability of the solution in the reactor under boiling nitric acid during the dissolution process, it has become a key research topic in various countries. According to the criticality safety problem of nuclear fuel dissolution process, the criticality effect of nitric acid concentration was studied. The criticality experiment data of nuclear fuel dissolution process were obtained by keeping the concentration of nitric acid in the same fuel concentration. Four experiments were conducted with different concentrations of nitric acid. During the experiment, the subcritical extrapolation method, reactivity interpolation method, and stable power method were used to complete the criticality experiment. The experimental results show that with the increase of nitric acid concentration, the relative deviation of the criticality experiment data is 0.068%, and the relative deviation between the criticality experiment results and the theoretical calculated values is 0.39%. The research results show that the reactivity of the system gradually increases as the concentration of nitric acid decreases. Therefore, it is necessary to consider the reactivity changes caused by changes in the criticality safety of the spent fuel dissolution process, and high attention is needed. According to the agreement between the experiment and the theoretical calculation, it is appropriate to use the Monte Carlo code MONK to calculate and analyze the acidity effect of the solid-liquid two-phase solution system, which can be used as a nuclear criticality safety control engineering design process for the solid-liquid two-phase nuclear fuel dissolution system. This series of experiment data can be used for calculation, verification, and safety evaluation of critical analysis under solid-liquid coexistence conditions of nuclear fuel. This paper results provide data support for improving the criticality safety control level of critical post-processing equipment.

This study proposes a teaching resource recommendation method (TRRDLMF) based on deep learning and probabilistic matrix decomposition, aiming to improve teaching resource recommendation’s accuracy and personalization level. The study combines hybrid neural network feature extraction of teaching resources and user feature extraction based on extended noise-reducing self-encoder and extended probabilistic matrix decomposition-based teaching resource recommendation technique. The study validates the model’s effectiveness by conducting empirical analyses on four online learning platform datasets of different sizes. The recommendation system can effectively track learners’ knowledge mastery status and learning preferences, and provide corresponding teaching resources. Test question similarity and difficulty analysis results show that the model can accurately capture the correlation between test questions and provide complementary data in education. The personalized recommendation analysis reveals the learners’ knowledge preference states that change with learning, demonstrating the model’s ability to give explanations at the level of learners’ knowledge preferences. The analysis of the impact of data size on recommendation results shows that the recommender system can achieve up to 73.12% accuracy and 97.89% recall for different TOP-K recommendation lists, with the best F-value at TOP-6. The personalized recommendation system for teaching resources based on the joint probability matrix decomposition model and CNN improvement algorithm proposed by the research demonstrates significant effects in improving the accuracy and personalization level of teaching resources recommendation, which helps learners to acquire suitable learning resources more efficiently, and has high practical value and promotion potential.

Micro-pore structure affects the fluid storage and seepage in coal seams.In this paper, six samples from the Jurassic Yan'an Formation coal seam in the Shenmu area of the Ordos Basin were taken as the object of study.The pore distribution characteristics of coal seams were jointly characterized by NMR, CO2 adsorption and N2 adsorption at multiple scales, and the connectivity and homogeneity of microscopic pores were investigated by combining multi-scale joint characiterization with CT scanning.Results show that the micro-pores of coal are the main contributors to the specific surface area and pore volume, followed by meso-pores.There is a good uniformity in the pore size distribution of the micro-pores and meso-pores by combing NMR and adsorption, while considerable differences are found in the macro-pores.Displacement NMR and CT excel in reflecting the degree of connectivity, both of which are consistent in the characterization of connectivity.Parameters such as coordination number and seepage pore ratio can effectively reflect the degree of connectivity of the sample, whose patterns of connectivity is M6>M2>M12>M15>M10>M4.The saturation of bound water shows a satisfactory positive correlation with pore-throat ratio of coal samples.It can be seen that the pore structure has a great influence on the degree of fluid migration, which is the basis for studying and evaluating gas occurrence and seepage.