The discovery that blazars dominate the extra-galactic $\gamma$-ray sky is a triumph in the Fermi era. However, the exact location of $\gamma$-ray emission region still remains in debate. Low-synchrotron-peaked blazars (LSPs) are estimated to produce high-energy radiation through the external Compton process, thus their emission regions are closely related to the external photon fields. We employed the seed factor approach proposed by Georganopoulos et al. It directly matches the observed seed factor of each LSP with the characteristic seed factors of external photon fields to locate the $\gamma$-ray emission region. A sample of 1 138 LSPs with peak frequencies and peak luminosities was adopted to plot a histogram distribution of observed seed factors. We also collected some spectral energy distributions (SEDs) of historical flare states to investigate the variation of $\gamma$-ray emission region. Those SEDs were fitted by both quadratic and cubic functions using the Markov-chain Monte Carlo method. Furthermore, we derived some physical parameters of blazars and compared them with the constraint of internal $\gamma\gamma$-absorption. We find that dusty torus dominates the soft photon fields of LSPs and most $\gamma$-ray emission regions of LSPs are located at 1–10 pc. The soft photon fields could also transition from dusty torus to broad line region and cosmic microwave background in different flare states. Our results suggest that the cubic function is better than the quadratic function to fit the SEDs.

The assessment of seed quality and physiological potential is essential in seed production and crop breeding. In the process of rapid detection of seed viability using tetrazolium (TZ) staining, it is necessary to spend a lot of labour and material resources to explore the pretreatment and staining methods of hard and solid seeds with physical barriers. This study explores the TZ staining methods of six hard seeds (Tilia miqueliana, Tilia henryana, Sassafras tzumu, Prunus subhirtella, Prunus sibirica, and Juglans mandshurica) and summarizes the TZ staining conditions required for hard seeds by combining the difference in fat content between seeds and the kinship between species, thus providing a rapid viability test method for the protection of germplasm resources of endangered plants and the optimization of seed bank construction. The TZ staining of six species of hard seeds requires a staining temperature above 35 °C and a TZ solution concentration higher than 1%. Endospermic seeds require shorter staining times than exalbuminous seeds. The higher the fat content of the seeds, the lower the required incubation temperature and TZ concentration for staining, and the longer the staining time. And the closer the relationship between the two species, the more similar their staining conditions become. The TZ staining method of similar species can be predicted according to the genetic distance between the phylogenetic trees, and the viability of new species can be detected quickly.

The laboratory generation and diagnosis of uniform near-critical-density (NCD) plasmas play critical roles in various studies and applications, such as fusion science, high energy density physics, astrophysics as well as relativistic electron beam generation. Here we successfully generated the quasistatic NCD plasma sample by heating a low-density tri-cellulose acetate (TCA) foam with the high-power-laser-driven hohlraum radiation. The temperature of the hohlraum is determined to be 20 eV by analyzing the spectra obtained with the transmission grating spectrometer. The single-order diffraction grating was employed to eliminate the high-order disturbance. The temperature of the heated foam is determined to be T = 16.8 ± 1.1 eV by analyzing the high-resolution spectra obtained with a flat-field grating spectrometer. The electron density of the heated foam is about $N_e=4.0\pm 0.3\times {10}^{20}{\text{cm}}^{-3}$ under the reasonable assumption of constant mass density.

Measures of uncertainty are a topic of considerable and growing interest. Recently, the introduction of extropy as a measure of uncertainty, dual to Shannon entropy, has opened up interest in new aspects of the subject. Since there are many versions of entropy, a unified formulation has been introduced to work with all of them in an easy way. Here we consider the possibility of defining a unified formulation for extropy by introducing a measure depending on two parameters. For particular choices of parameters, this measure provides the well-known formulations of extropy. Moreover, the unified formulation of extropy is also analyzed in the context of the Dempster–Shafer theory of evidence, and an application to classification problems is given.

The ongoing pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to an unprecedented global public health crisis. The objectives of this study were to analyse the dynamic trend in specific antibodies in the serum of patients infected with SARS-CoV-2 within 12 months after recovery and to make a preliminary assessment of the protective effect of vaccination. Eighty-seven patients with confirmed COVID-19 who were admitted to our hospital from January to February 2020 were followed after recovery. Three-millilitre blood samples were collected for specific antibody detection at four time points: 1, 6 and 12 months after recovery and 1 month after vaccination. The changes in specific immunoglobulin G (IgG) antibody and total antibody levels over 12 months were analysed. Moreover, an independent comparison of the neutralising antibody levels of patients after vaccination with those of healthy medical staff after vaccination was performed to compare the inhibition rates of the neutralising antibody to the virus. No statistically significant difference in the sex distribution between groups was observed (P > 0.05). Older patients had a greater risk of developing severe and critical COVID-19 (P < 0.05). The percentages of subjects positive for IgG antibodies at 1, 6 and 12 months after recovery were 88.5%, 75.9% and 50.6%, respectively. The rate of IgG antibody conversion from positive to negative was not uniform across time points: the change was slow in the first 6 months but increased significantly in the last 6 months (P < 0.05). The positive rate of critically ill patients in the first 6 months was 100.0%. The trend over time in total antibody levels was similar to that of IgG antibody levels. Over 12 months, the sample/cut off value of total antibodies continued to decrease, while that of different disease severities was significantly different (P < 0.05). After vaccine administration, the total antibody level exceeded the detection level in the first month, which was independent of disease severity (P > 0.05). Significant differences were observed in the inhibition rate of the neutralising antibody against the virus in the disease group and the control group (P < 0.05). IgG antibody produced by patients naturally infected with SARS-CoV-2 has a duration of no less than 1 year, and the change trend graph of total antibody levels was the same as that of IgG antibody levels. Under vaccine stimulation, the positive rate of IgG antibody was as high as 100%, and the total antibody concentration reached the highest level, which was independent of disease severity. Neutralising antibodies following vaccination in patients who recovered from COVID-19 had a higher inhibition rate against SARS-CoV-2 than those of vaccinated healthy controls, indicating that these COVID-19 patients had a lower risk of reinfection and were better protected.