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The current employment situation is getting tighter and tighter, and innovation and entrepreneurship of college students have gradually become the focus of attention of the government and colleges and universities. This paper preprocesses the student data, constructs the data matrix using the gray prediction algorithm, uses the least squares method, establishes the differential equation solution, and obtains employment prediction data. For the employment prediction can be known to the innovation and entrepreneurship situation of college students, this paper further introduces the Logistic regression analysis, establishes a multivariate regression analysis algorithm based on the influencing factors of innovation and entrepreneurship, and provides theoretical support for the study of the influencing factors and the optimization mechanism of the management of innovation and entrepreneurship student management. This paper takes University H in Zhejiang Province of China as the research site to explore the current situation of innovation and entrepreneurship of its college students in depth. The students who choose self-help entrepreneurship in 2022-2023 only accounted for 2.42% and 2.04%, and the predicted percentage in 2024 is 1.93%, so the current situation of innovation and entrepreneurship is dismal. In the analysis of college students’ innovation and entrepreneurship influencing factors, the factors of specialty, personal work experience, and buddy entrepreneurship experience all showed significant differences (P

With the rapid development of information media, senior counselors face many new opportunities and challenges in ideological and political education discourse. This study divides the counselor discourse modal system into linguistic and visual image modal. Adopting the advanced Transformer architecture and combining the BERT and RoBERTa algorithms, this paper profoundly analyzes the syntactic structure in the discourse. It extracts the emotional features in the text using the bert word vector model. Meanwhile, the dynamic features in the audio information of the discourse are extracted by MFCC technique. After completing the preprocessing of discourse features, we used Bayesian classifier for classification and recognition to further refine the annotation of discourse information. The study results showed that the overall sentiment of the discourse of tutor number 1 tended to be harmful during the 30 minutes, with six segments having an emotional pleasantness of more than -2. In addition, the density of positive discourse sentiment of tutor number 3 was 0.0811 higher than that of tutor number 4. In contrast, the number of discourse labeling of tutor number 5 was reduced by 74 times. Through in-depth analysis and understanding of these discourse modalities and affective features, tutors can better adapt to the information media environment and effectively carry out ideological and political education work.

The recent major worldwide outbreak of monkeypox virus (MPXV) has highlighted the urgent need for accurate MPXV detection methods. Although quantitative PCR (qPCR) technique is currently the gold standard for MPXV diagnosis, the high costs associated with the technique and the need for complex instrumentation, limits its application in resource‐poor settings. CRISPR technology has developed rapidly in recent years and provides an effective tool for point‐of‐care testing pathogen identification. Here, we exploited the cleavage properties of the Cas12a enzyme and Cas13a enzyme, to detect the MPXV specific genes, F3L gene and B6R gene, respectively. We developed two detection protocols: a 2‐step method in which the CRISPR Dual System reaction and the multiplex recombinase polymerase amplification reaction were carried out in separate tubes and a single‐tube method in which both reactions were carried out in one tube. Evaluation of the two methods showed that our protocol can detect the MPXV genome down to 10° copies/μL with good specificity and no cross‐reactivity with other poxviruses pseudoviruses, and bacteria. Mock positive samples were used to assess clinical applicability, with the results showing satisfactory concordance with the qPCR method for parallel testing. In conclusion, our study provides a reliable molecular diagnostic strategy for detection of MPXV. [ABSTRACT FROM AUTHOR]

Handan is one of the most polluted coal mining cities in the North China Plain (NCP). There is a lack of research on the pollution characteristics and sources of carbonaceous components in PM2.5 in Handan city. Atmospheric PM2.5 samples were collected from Handan City during 2018 and the organic carbon (OC) and elemental carbon (EC) in PM2.5 were analyzed with a carbon analyzer. The annual average mass concentrations of PM2.5 and total carbon (TC = OC + EC) in Handan were (101.88 ± 79.01) μg/m3 and (28.03 ± 23.28) μg/m3, respectively. The annual average ratio of TC/PM2.5 was (28.29% ± 7.95%), indicating that carbonaceous components made a major contribution to PM2.5. The seasonal variations of OC and EC concentrations in PM2.5 were consistent with PM2.5, which was higher in winter and lower in summer. The annual average OC/EC ratio was (10.33 ± 5.83), and the (OC/EC)min ratio for each season was greater than 2, suggesting that there was probably secondary organic carbon (SOC) formation all around the year. The correlations between OC and EC during spring and winter were much more significant than during summer and autumn, which indicated that the sources of OC and EC in summer and autumn were more complex. Principal component analysis (PCA) displayed that the main sources of carbonaceous components in PM2.5 were coal combustion emission, road dust and vehicle exhaust, which may be related to coal-fired power generation and steelmaking, and coal transportation in Handan city. The potential source contribution function (PSCF) analysis demonstrated that PM2.5 and carbonaceous components in Handan city were significantly influenced by both local emissions and regional transport during the observation period. [ABSTRACT FROM AUTHOR]

Aims: To evaluate the antidepressant‐like effect of compound GW117 in rodents using in vitro binding and uptake assays as well in vivo behavioral tests. Methods: We investigated the target profile of GW117 using [35S]‐GTPγS and [3H]PIP binding. Using the forced swimming test and chronic unpredictable stress in rats, tail suspension test in mice and rats, and learned helplessness model in mice, we further revealed the antidepressant‐like and anxiolytic‐like effects of GW117. Results: The current study suggests that GW117 displays serotonin 2C (5‐HT2C) receptor antagonist and melatonin type 1 and 2 (MT1/MT2) receptor agonist properties, as well as evident antidepressant and anxiolytic effects. Conclusion: These data suggest that GW117 is probably a potent antidepressant. [ABSTRACT FROM AUTHOR]