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The photodissociation dynamics of the hydrogen sulfide cation (H2S+) (X2B1) were investigated using the time-sliced velocity map ion imaging technique. S+ (4Su) product images were measured at four photolysis wavelengths around 393.70 nm, corresponding to the excitation of the H2S+ (X2B1) cation to the A2A1 (0, 8, 0) state. The raw images and the derived total kinetic energy releases (TKERs) spectra exhibited partial rotational resolution for the H2 products. A sensitive dependence on the photolysis wavelength was observed in the TKER spectra and anisotropy parameters. Within a narrow excitation energy range of ∼12 cm−1, the H2 products showed two distinct rotational excitations. Furthermore, clear differences in anisotropy parameters were observed. These phenomena indicate that the rotational excitation of the H2S+ ions plays a role in the non-adiabatic photodissociation dynamics. [ABSTRACT FROM AUTHOR]

N6-methyladenosine (m6A), a well-characterized RNA modification, is involved in regulating multiple biological processes; however, genome-wide identification and functional characterization of the m6A modification in legume plants, including soybean (Glycine max (L.) Merr.), remains lacking. In this study, we utilized bioinformatics tools to perform comprehensive analyses of molecular writer candidates associated with the RNA m6A modification in soybean, characterizing their conserved domains, motifs, gene structures, promoters, and spatial expression patterns. Thirteen m6A writer complex genes in soybean were identified, which were assigned to four families: MT-A70, WTAP, VIR, and HAKAI. It also can be identified that multiple cis elements in the promoters of these genes, which were classified into five distinct groups, including elements responsive to light, phytohormone regulation, environmental stress, development, and others, suggesting that these genes may modulate various cellular and physiological processes in plants. Importantly, the enzymatic activities of two identified m6A writers, GmMTA1 and GmMTA2, were confirmed in vitro. Furthermore, we analyzed the expression patterns of the GmMTAs and GmMTBs under different abiotic stresses, revealing their potential involvement in stress tolerance, especially in the response to alkalinity or darkness. Overexpressing GmMTA2 and GmMTB1 in soybean altered the tolerance of the plants to alkalinity and long-term darkness, further confirming their effect on the stress response. Collectively, our findings identified the RNA m6A writer candidates in leguminous plants and highlighted the potential roles of GmMTAs and GmMTBs in the response to abiotic stress in soybean.

Objective: To achieve accurate application of kappa-carrageenan as a gelling agent in food industries such as processed meats, dairy, desserts and jellies, as well as seamless capsule in pharmaceuticals and crushable beads in tobaccos. Methods: The viscosities of kappa-carrageenan solution prepared at different hydration temperature, different dosages of kappa-carrageenan dosage and potassium chloride were measured by digital viscometer. Results: ① The hydration temperature had a great influence on the viscosity of kappa-carrageenan gel solution. With the increasing hydration temperature （fixed hydration time at 1 h）, the viscosity of kappa-carrageenan gel solution decreased. Generally the higher the dosage of kappa-carrageenan, the greater the decrease of viscosity. ② The viscosity of kappa-carrageenan solution increased exponentially with increasing dosage. ③ The presence of KCl had little effect on the viscosity at low dosage of kappa-carrageenan. However, the viscosity of kappa-carrageenan solutions at higher dosages increased with the increasing KCl dosage. Conclusion: Hydration temperature and gel dosage had important effects on the viscosity of kappa-carrageenan, while the amount of potassium chloride had relatively little effect on the viscosity.

The identification and analysis of quantum state-specific effects can significantly deepen our understanding of detailed photodissociation dynamics. Here, we report an experimental investigation on the vibrational state-mediated photodissociation of the OCS+ cation via the A2Π1/2 (ν1 0 ν3) states by using the velocity map ion imaging technique over the photolysis wavelength range of 263–294 nm. It was found that the electronically excited S+ product channel S+(2Du) + CO (X1Σ+) was significantly enhanced when the ν1 and ν3 vibrational modes were excited. Clear deviations in the branching ratios of the electronically excited S+ channel were observed when the vibrational modes ν1 and ν3 were selectively excited. The results reveal that vibrationally excited states play a vital role in influencing the nonadiabatic couplings in the photodissociation process. [ABSTRACT FROM AUTHOR]

To delve into the microscopic property of the cluster RhSin (n = 6–15), this study employs the CALYPSO structure prediction program and density functional theory. The paper conducts a comprehensive theoretical analysis of the clusters, examining parameters such as structures, relative stabilities, charge transfer, vertical electron affinity, vertical ionization potential, chemical potential, chemical hardness, and infrared and Raman spectra. The optimization process reveals that the rhodium doping has clearly changed the structures of silicon clusters. The ground state geometries favor Rh-linked framework beginning from n = 6, and they favor Rh-encapsulated Si cages when n approach 10. RhSi13 cluster is more stable than its neighbors. The charges transfer within the clusters always transfer from silicon atom to rhodium atom, and there is spd hybridization in RhSin cluster. The analyzed chemical potential and chemical hardness pointed out the RhSi13 cluster has the stronger hardness than other clusters. At last, the infrared and Raman spectrum properties for RhSi13 cluster are analyzed. [ABSTRACT FROM AUTHOR]

In the federated average algorithm,the weight update is used to update the global model.The algorithm only considers the size of the data volume of each client when the weight is updated,and does not consider the impact of data quality on the mo-del.An improvement based on analytic hierarchy is proposed.The federated averaging algorithm is the first to process multi-source data from the perspective of data quality.First,the entropy method is used to calculate the importance of each attribute in the data,and it is used as the value of the criterion layer in the level analysis to calculate the data of each client quality.Then,combined with the amount of data on the client,the weight update method is recalculated in the global model.The simulation results show that for small and medium data sets,the model trained with support vector machines has the highest accuracy,rea-ching 85.7152%.For large data sets,the model trained with random forest has the highest accuracy,reaching 91.9321%.Compared with the traditional federal average method,the accuracy rate is increased by 3.5% on small and medium data sets and 1.3% on large data sets,which can improve the accuracy of the model while improving the security of the data and model.