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This article focuses on deriving the averaging principle for Hilfer fractional stochastic evolution equations (HFSEEs) driven by Lévy noise. We show that the solutions of the averaged equations converge to the corresponding solutions of the original equations, both in the sense of mean square and of probability. Our results enable us to focus on the averaged system rather than the original, more complex one. Given that the existing literature on the averaging principle for Hilfer fractional stochastic differential equations has been established in finite-dimensional spaces, the novelty here is the derivation of the averaging principle for a class of HFSEEs in Hilbert space. Furthermore, an example is allotted to illustrate the feasibility and utility of our results.

Avian infectious bronchitis is a serious and highly contagious disease that is caused by the infectious bronchitis virus (IBV). From January 2021 to June 2022, 1008 chicken tissue samples were collected from various regions of southern China, and 15 strains of the IBV were isolated. Phylogenetic analysis revealed that the strains mainly comprised the QX type, belonging to the same genotype as the currently prevalent LX4 type, and identified four recombination events in the S1 gene, among which lineages GI-13 and GI-19 were most frequently involved in recombination. Further study of seven selected isolates revealed that they caused respiratory symptoms, including coughing, sneezing, nasal discharge, and tracheal sounds, accompanied by depression. Inoculation of chicken embryos with the seven isolates resulted in symptoms such as curling, weakness, and bleeding. Immunization of specific pathogen-free (SPF) chickens with inactivated isolates produced high antibody levels that neutralized the corresponding strains; however, antibodies produced by vaccine strains were not effective in neutralizing the isolates. No unambiguous association was found between IBV genotypes and serotypes. In summary, a new trend in IBV prevalence has emerged in southern China, and currently available vaccines do not provide protection against the prevalent IBV strains in this region, facilitating the continued spread of IBV.

Calcium and magnesium are major nutrient elements of plants, and both play an important role in plant growth and development. Pinus massoniana and P. hwangshanensis are important afforestation tree species in barren mountains in China. However, observation and research on calcium and magnesium nutrition of dominant forest species in China are still limited. This study determined the concentration of calcium and magnesium in needles for two species from five sites in East China by inductively coupled plasma optical emission spectrometry (ICP-OES). We then explored the inter- and intra-population variation pattern of calcium and magnesium and their relationship with environmental factors. There were significant differences in traits among populations. The strongest factors, which impacted the variation of calcium and magnesium concentration, were elevation and individual differences, respectively. Element concentration was correlated to environmental factors such as longitude, latitude, elevation, and mean annual temperature. The results of this study can be helpful for a better understanding of tree growth, population survival, and forest succession.

With the promotion of carbon peaking and carbon neutrality goals and the construction of renewable-dominated electric power systems, renewable energy will become the main power source of power systems in China. How to ensure the accommodation of renewable energy will also be the core issue in the future development process of renewable-dominated electric power systems. In this context, shared energy storage (SES), a novel business model combined with energy storage technologies and the sharing economy, has the potential to play an important role in renewable energy accommodation scenarios. This paper systematically organizes the application prospect, development status and key technologies of SES in the renewable energy accommodation scenario in the context of China, providing helpful references for the promotion of the business model. Firstly, a typical SES framework for renewable energy accommodation is described, and three basic forms of SES in this scenario are presented. Moreover, the application prospect of SES in the renewable energy accommodation scenario is quantitatively analyzed based on the renewable energy generation planning under the carbon peaking goal and the current guarantee mechanism of renewable energy accommodation. Furthermore, the rules for energy storage systems that provide the peak-regulation ancillary service in typical regions and provincial administrative regions in China are summarized, and the development status of SES in the renewable energy accommodation scenario is analyzed, combined with the actual market data. Finally, the key technologies to promote the further development of SES for renewable energy accommodation are presented.

A self-contained MEMS vector hydrophone with a scalar–vector integrated design is proposed in this paper. Compared with traditional MEMS vector hydrophones, this design solves the problem of ambiguity in the port and starboard during orientation, and also realizes the self-contained storage of acoustic signals. First, the sensor principle and structural design of the self-contained MEMS hydrophone are introduced, and then the principle of the combined beamforming algorithm is given. In addition to this, the amplitude and phase calibration method based on the self-contained MEMS vector hydrophone is proposed. Then, the sensitivity and phase calibrations of the sensor are carried out in the standing wave tube. The sensitivity of the vector channel is −182.7 dB (0 dB@1 V/μPa) and the sensitivity of the scalar channel is −181.8 dB (0 dB@1 V/μPa). Finally, an outdoor water experiment was carried out. The experimental results show that the self-contained MEMS vector hydrophone can accurately pick up and record underwater acoustics information. It realizes the precise orientation of the target by combining beamforming algorithms. The direction of arrival (DOA) error is within 5° under the outdoor experimental conditions with an SNR of 13.67 dB.

Species diversity (SD) and genetic diversity (GD) are the two basic levels of biodiversity. In general, according to the consensus view, the parallel effects of environmental heterogeneity, area, and connectivity on two levels, can drive a positive correlation between GD and SD. Conversely, a negative correlation or no correlation would be expected if these effects are not parallel. Our understanding of the relationships between SD and GD among different ecosystems, sampling methods, species, and under climate change remains incomplete. In the present study, we conducted a hierarchical meta-analysis based on 295 observations from 39 studies and found a positive correlation between genetic diversity and species diversity (95% confidence interval, 7.6–22.64%). However, significant relationships were not found in some ecosystems when we conducted species–genetic diversity correlation analysis based on a single ecosystem. Moreover, the magnitudes of the correlations generally decreased with the number of sampling units and the annual average the temperature of sampling units. Our results highlight the positive correlation between GD and SD, thereby indicating that protecting SD involves protecting GD in conservation practice. Furthermore, our results also suggest that global increases in temperature during the 21st century will have significant impacts on global biodiversity.

Characterizing the physical and chemical properties of two-dimensional (2D) materials is of great significance for performance analysis and functional device applications. As a powerful characterization method, nonlinear optics (NLO) spectroscopy has been widely used in the characterization of 2D materials. Here, we summarize the research progress of NLO in 2D materials characterization. First, we introduce the principles of NLO and common detection methods. Second, we introduce the recent research progress on the NLO characterization of several important properties of 2D materials, including the number of layers, crystal orientation, crystal phase, defects, chemical specificity, strain, chemical dynamics, and ultrafast dynamics of excitons and phonons, aiming to provide a comprehensive review on laser-based characterization for exploring 2D material properties. Finally, the future development trends, challenges of advanced equipment construction, and issues of signal modulation are discussed. In particular, we also discuss the machine learning and stimulated Raman scattering (SRS) technologies which are expected to provide promising opportunities for 2D material characterization.