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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.

Modified polyvinylidene chloride (PVDC) resin was prepared using octafluoropentyl methacrylate and trimethylolpropane trimethacrylate as modifying monomers through seeded emulsion polymerization. The successful incorporation of octafluoropentyl methacrylate into the PVDC resin was confirmed by Fourier transform infrared spectroscopy (FTIR) and X‐ray photoelectron spectroscopy (XPS) analyses. Scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and XPS were utilized to investigate the element distribution in the modified monomer emulsion and the mechanism of monomer modification. The results demonstrated that the fluorine monomer was reacted in the resin, and mainly concentrated on the surface of the resin. The addition of octafluoropentyl methacrylate and trimethylolpropane trimethacrylate improved the water resistance of the resin. Compared to unmodified PVDC resin, the contact angle of the modified PVDC resin increased from 89.46° to 109.51°, and the water resistance at room temperature increased from 120 to 500 h. Furthermore, the modified resin exhibited excellent mechanical properties, thermal stability, and storage stability. [ABSTRACT FROM AUTHOR]

Topological insulators are characterized by exhibiting an internal insulating state but a surface conductor state, which makes them advantageous for applications in novel devices. However, for most given acoustic topological metamaterials, the operating frequency is relatively fixed and the effect of temperature on their topological properties is rarely considered. Therefore, a temperature-tunable acoustic topological insulator is constructed in this paper. The quadruple degenerate Dirac cone formed at Γ point can be opened by adjusting the temperature, causing topological band inversion between the doubly degenerate dipolar and quadrupole states, and achieving topological phase transition. The evolution of its topological state with temperature is numerically investigated and a novel topological acoustic waveguide is constructed. The switching effect of temperature on the waveguide device is verified by numerical simulation and experiment. Non-contact active modulation of edge states in the structure is achieved by temperature-controlled topological phases, exhibiting acoustic switching effects. This study can provide corresponding references for the intelligent control of acoustic topology in noise, vibration, and other aspects. [ABSTRACT FROM AUTHOR]

Modeling user intention with limited evidence in short-term historical sequences is a major challenge in session recommendation. In this domain, research exploration extends from traditional methods to deep learning. However, most of them solely concentrate on the sequential dependence or pairwise relations within the session, disregarding the inherent consistency among items. Additionally, there is a lack of research on context adaptation in session intention learning. To this end, we propose a novel session-based model named C-HAN, which consists of two parallel modules: the context-embedded hypergraph attention network and self-attention. These modules are designed to capture the inherent consistency and sequential dependencies between items. In the hypergraph attention network module, the different types of interaction contexts are introduced to enhance the model's contextual awareness. Finally, the soft-attention mechanism efficiently integrates the two types of information, collaboratively constructing the representation of the session. Experimental validation on three real-world datasets demonstrates the superior performance of C-HAN compared to state-of-the-art methods. The results show that C-HAN achieves an average improvement of 6.55%, 5.91%, and 6.17% over the runner-up baseline method on Precision@K, Recall@K, and MRR evaluation metrics, respectively. [ABSTRACT FROM AUTHOR]

AbstractWe conducted this meta-analysis to investigate neurological toxicities with poly (ADP-ribose) polymerase inhibitors (PARPis) in cancer patients. Databases were searched for randomized controlled trials (RCTs) from 1 January 2000 to 1 November 2023. Forty-six RCTs and 9529 patients were included. PARPis could increase the risk of all-grade headache [risk ratio (RR), 1.22; 95% confidence intervals (CI), 1.14–1.30; P < 0.00001], dizziness (RR, 1.40; 95% CI, 1.28–1.53; P < 0.00001), dysgeusia (RR, 1.93; 95% CI, 1.44–2.60; P < 0.0001) and insomnia (RR, 1.32; 95% CI, 1.09–1.60; P < 0.0001) in cancer patients. Headache was the most common neurological toxicity. Niraparib was associated with a higher risk of headache and insomnia, talazoparib with a higher risk of dizziness and rucaparib with a higher risk of dysgeusia. Breast cancer patients receiving PARPis have a higher risk of dysgeusia, while ovarian cancer patients are at an increased risk of insomnia. PARPis may increase the risk of mild to moderate neurological toxicities, but not severe ones. [ABSTRACT FROM AUTHOR]

Double-layer island working face main roadway coal pillars are affected by complex mining stress superposition, when different coal pillar width combinations, the surrounding rock stress field will produce different degrees of regional loading increase effect; the study of the surrounding rock stress field regional superposition loading increase law is meaningful to explaining the failure mode of the roadway and determining the critical control area. This study combines numerical simulation with on-site monitoring and other methods and draws the following conclusions: The superimposed loading increase law (“decreasing” → “increasing”) of the abutment pressure and deviatoric stress in the lower coal seam of the double-layer island working face during the mining; the type of the principal stress deflection in the advance working face region; and by obtaining the three types of development morphology of the deviatoric stress peak zone of the roadway and its corresponding nine evolution modes (one type of circular tube → four types of inverse hyperbolic body → four types of hyperbolic body) in the double-layered island working face mining. Indicated the critical reinforcement area corresponding to the main roadway when at different combinations of coal pillar widths; determined the main track roadway protective coal pillars width for 40 m and the shape of the roadway peak deviatoric stress zone is the inverse class hyperbolic body mode; according to the evolution mode of the peak deviatoric stress zone, determined the synergistic failure control program for the asymmetric critical zone of the roadway surrounding rock which is a targeted scientific support method; after the feedback of on-site monitoring and, the support program is reasonable and effective. [ABSTRACT FROM AUTHOR]