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The cultivation path of the applied “dual-teacher” teacher team in this paper mainly relies on the qualification standard and evaluation system. Big data technology is used to collect data, deeply mine fragmented data, and further extract index factors that affect the quality of teachers. The multi-level fuzzy hierarchical evaluation model realizes the quantification of the decision-making process with less quantitative information, and determines the weights through the multi-level comparison of importance, to test and evaluate the teaching ability of “dual-teacher” teachers. The results show that, among the 166 survey respondents, 77 respondents belong to the “ Dual-teacher” teachers, accounting for about 45.03%. The primary needs and ways for most of the teachers to participate in the training of “dual-teacher” teachers are to improve the practical ability of industry and enterprise positions (score 0.86) and the school-based training of dual-teacher teachers (0.93), which is centralized in the college. In evaluating “dual-teacher” teaching, the weight of industry-teaching integration is 0.3378, so the ability of industry-teaching integration is a more meaningful indicator. College students are satisfied with “dual-teacher teaching”, and the score shows that the essential satisfaction is more than half of the total number of samples, which is 343.

As a core course of educational technology, the teaching of application software in colleges and universities faces the problem of insufficient practical ability of learners. This paper constructs a suitable path of computer software application teaching with reinforcement learning by combining reinforcement learning algorithm with students’ cognitive diagnosis theory. Students’ practical level is diagnosed through students’ actual operation results combined with the factors of guessing and mistakes, and appropriate teaching practice paths are recommended based on students’ practical ability combined with Markov decision-making to model the environment of computer software application practice. The TOVE method was used to evaluate the computer application practice course, and the practice paths with individualization were reasoned based on the connection between students’ knowledge points. The results show that among the experimental results of different practice paths, the effectiveness of the deep learning practice path of S1 is the highest at 85%. Compared with the expert-recommended practice path, the deviation value of the path effectiveness of S5 is 1, which indicates that the deep learning practice path is similar to the expert path likewise with a certain degree of specialization. On the Analysis of classroom project practice, the deviation value of the control class is 0.5512, and the deviation value of the experimental class is 4.2662, which is significantly larger than that of the control class, indicating that there is a significant improvement in students’ practical ability under the deep learning teaching practice path.

Context: High-pressure chemistry has advantages in exploring novel energetic materials and is the key to the development of new high-energy materials. The complexity and danger of experimental processes require a deeper understanding by advanced simulation techniques. Therefore, a high-precision comparative DFT-D study was performed to investigate the effect of pressure on series of catenated nitrogen energetic crystals. The results show that there exist phase transitions for N4, N8, and N10 at 4 GPa, 3 GPa, and 2 GPa respectively, which are embodied in various properties of these crystals. Studies on band gap and DOS indicate pressure-induced improvement on the ability for electrons transition from occupied orbitals to empty ones. Hirshfeld surface analysis qualitatively suggests that hydrogen bonding interactions are becoming dominant inter-molecular interactions. The topological analysis quantitatively reveals that pressure is beneficial to enhancing the inter-molecular hydrogen bonding energy, thereby playing an important role in the stability of high-pressure phases. The discussions on mechanical properties imply that pressure can improve the rigidity of these energetic systems and enhance their mechanical properties. Our findings evidence the high-pressure phase transitions for catenated nitrogen energetic crystals, which lay the theoretical foundation for the development of novel energetic materials. Methods: Series of catenated nitrogen energetic crystals N4, N8 and N10 were obtained from experiments. Optimizations were performed by GGA/PBE functional and G06 dispersion correction within the framework of CASTEP code, and the cutoff energies of the plane waves were set to 700 eV. The particular moiety in the crystals was extracted by Multiwfn 3.6 and subsequent analysis was conducted by Gaussian 09W package. [ABSTRACT FROM AUTHOR]

Background and Aims: There are still no useful biomarkers for the prognosis of esophageal squamous cell carcinoma (ESCC). In the prognosis of some kinds of cancer, soluble programmed death 1 (sPD‐1) and programmed death ligand 1 (sPD‐L1) have demonstrated statistical significance, but the prognostic value of serum sPD‐L1 and sPD‐1 remains unclear in ESCC. Methods: Here, a meta‐analysis was performed to estimate the prognostic value of sPD‐L1 and sPD‐1 in ESCC. To obtain eligible studies, we searched mainstream databases (PubMed, Cochrane, Embase, Web of Science, Wanfang Data, and CNKI), and the survival data including hazard ratios (HR) and its 95% confidence intervals (95% CI) from included literature were extracted. Results: Six articles were included, including 645 patients with ESCC. The statistical result of this meta‐analysis indicated that serum sPD‐1 had no significant correlation with overall survival (OS) of patients with ESCC (p > 0.05). Patients with ESCC with high concentrations of serum sPD‐L1 demonstrated a significantly poor prognosis (HR = 1.73, 95% CI: 1.42–2.11, p < 0.001). Conclusion: Higher levels of serum sPD‐L1 may predict poor OS in ESCC patients, which may be a promising and credible prognostic biomarker for esophageal cancer. [ABSTRACT FROM AUTHOR]

Sodium‐ion batteries (SIBs) and potassium‐ion batteries (PIBs) are considered the next‐generation candidates for future energy storage systems to partially substitute commercial lithium‐ion batteries because of their abundant sodium/potassium reserves, cost‐effectiveness, and high safety. Polyanionic cathode materials are widely used in alkali ion batteries due to their stable structural framework, high thermal stability, excellent alkali ion diffusion kinetics, and adjustable working voltage. Generally, the polyanionic cathodes used for SIBs surpass PIBs in the aspect of energy density and cycle life in most cases, however, the PIBs also have their unique advantages that are seldom reported. To this end, the polyanionic materials are classified by the valence states of active metal sites, the storage mechanism of Na+ and K+ in different crystal structures is summarized, and the electrochemical performance between SIBs and PIBs is compared. Particularly, some unique advantages of polyanionic cathodes in PIBs, such as high working voltage, superior rate capability, and excellent capacity retention are revealed, and the possible reasons are discussed in detail. Finally, various viable solutions are proposed to improve the battery performance of polyanionic compounds for future development. [ABSTRACT FROM AUTHOR]