Changes in mineral fraction and pore morphology of coal with acidification treatment: contribution of clay minerals to methane adsorption.

The accurate calculation of the contribution which provided by clay minerals in coal on methane adsorption not only bares a significant importance for evaluating the effectiveness of acid stimulation in improving permeability and estimating the coalbed methane reserves but also serves a guide for the governance and utilization of methane resources. In this study, hydrochloric acid (HCl) and hydrofluoric acid (HF) were used to remove specific minerals in Qingdong coal samples. We firstly analyzed the mineral compositions of coal samples with different acidification treatments based on the X-ray diffraction (XRD) experiments, together with analysis of the changes in pore morphology and adsorption capacity. The results showed that acidification did not significantly change the shape of the pores, which remained slit-/plate-like pore. However, the altered adsorption capacity of the coal samples was attributed to changes in pore structure and mineral distribution. Acid erosion of mesopores promoted the transition from mesopores to macropores, contributing to an increase of 8.4% and 24.36% in the percentage of macropores in coal samples treated with HCl and HF, respectively. Fractal dimension D1 grew from 2.2193 to 2.3888 and 2.2572, respectively, but D2 decreased from 2.6146 to 2.5814 and 2.5433, indicating an increment in pore surface roughness and a simplification of the pore structure. The mineral richness of the coal seams should be taken into consideration when applying acid stimulation to increase permeability due to that the acidification products may block the passage of gas migration when the mineral content is slight, which can hinder gas extraction. The aim of this study is to quantitatively determine the contribution rate of clay minerals in coal to methane adsorption with a calculation method is provided by combining pore parameters and limit adsorption capacity, resulting in a contribution rate of 15%.

Comparison of COVID-19 and seasonal influenza under different intensities of non-pharmaceutical interventions and vaccine effectiveness.

Background: The COVID-19 pandemic has lasted more than 2 years, and the global epidemic prevention and control situation remains challenging. Scientific decision-making is of great significance to people's production and life as well as the effectiveness of epidemic prevention and control. Therefore, it is all the more important to explore its patterns and put forward countermeasures for the pandemic of respiratory infections. Methods: Modeling of epidemiological characteristics was conducted based on COVID-19 and influenza characteristics using improved transmission dynamics models to simulate the number of COVID-19 and influenza infections in different scenarios in a hypothetical city of 100,000 people. By comparing the infections of COVID-19 and influenza in different scenarios, the impact of the effectiveness of vaccination and non-pharmaceutical interventions (NPIs) on disease trends can be calculated. We have divided the NPIs into three levels according to the degree of restriction on social activities (including entertainment venues, conventions, offices, restaurants, public transport, etc.), with social controls becoming progressively stricter from level 1 to level 3. Results: In the simulated scenario where susceptible individuals were vaccinated with three doses of COVID-19 coronaVac vaccine, the peak number of severe cases was 26.57% lower than that in the unvaccinated scenario, and the peak number of infection cases was reduced by 10.16%. In the scenario with level three NPIs, the peak number of severe cases was reduced by 7.79% and 15.43%, and the peak number of infection cases was reduced by 12.67% and 28.28%, respectively, compared with the scenarios with NPIs intensity of level 2 and level 1. For the influenza, the peak number of severe cases in the scenario where the entire population were vaccinated was 89.85%, lower than that in the unvaccinated scenario, and the peak number of infections dropped by 79.89%. Conclusion: The effectiveness of COVID-19 coronaVac vaccine for preventing severe outcomes is better than preventing infection; for the prevention and control of influenza, we recommend influenza vaccination as a priority over strict NPIs in the long term.

Influence of Film Role on the Positive Development of College Students' Entrepreneurial Behavior Using Positive Psychology.

To help College Students improve their entrepreneurial psychology and enrich their innovative achievements, this paper investigates College Students' entrepreneurial behavior based on the theory of positive psychology under the background of multiculturalism. Firstly, the background and development status of multiculturalism are expounded, and the main features of the multicultural era are pointed out; Secondly, the current situation is explained for College Students' mental health and entrepreneurial behavior, and the specific connotation of College Students' entrepreneurial psychology is summarized according to entrepreneurial behavior, including entrepreneurial consciousness, entrepreneurial will, entrepreneurial capability, and entrepreneurial personality; Thirdly, the positive effects of inspirational films and roles on the psychology of College Students are discussed. From the connotation of film and television culture, the main features of films are reviewed: intuitiveness, immediacy, universality, entertainment, and orientation. Finally, according to the psychological impact of inspirational films on College Students, a Questionnaire Survey (QS) is designed and distributed among the local College Students, and assumptions are put forward. The results show that the differences of College Students' entrepreneurial level are mainly reflected in gender, urban, and rural household registration, only-child-or-no, and entrepreneurial experience, and the gender differences are mainly in entrepreneurial consciousness, will, and personality (p < 0.05); There are significant differences in consciousness, will, capability, and personality between urban and rural household registration and entrepreneurial experience (p < 0.05); The differences between the only-child and non-only-child are obvious in three aspects: will, capability, and personality (p < 0.05). After the intervention of inspirational films, the average scores of all dimensions of the entrepreneurial level of students in the intervention group are 35.45, 36.41, 38.17, and 37.22, respectively, which have a certain improvement compared with the situation before the intervention. There are significant differences in the four dimensions (p < 0.05), which is statistically significant, indicating that the intervention of inspirational films has a positive impact on students' entrepreneurial level.

Mining of Movie Box Office and Movie Review Topics Using Social Network Big Data.

In order to solve the problems of high investment and low box office losses in the film industry, this study analyzes the topic of film box office and film and television reviews based on social network big data. Firstly, the factors that affect the box office of the movie are analyzed. Secondly, continuous and discrete feature parts, text parts, and fusion parts are merged. The box office prediction model of mixed features using deep learning is established, and the movie box office is predicted. Finally, compared with other algorithms and models, the box office prediction model of mixed features using deep learning is verified. The results show that compared with other models, the prediction accuracy of the mixed feature movie box office prediction model using depthwise separable convolution (DSC)-Transformer is higher than that of other algorithm models. Its optimal mean square error (MSE) value is 0.6549, and the optimal mean absolute error (MAE) value is 0.1706. The constructed model predicts the box office of nine movies, and the error between the predicted value and the true value is about 10%. Therefore, the established movie box office prediction model has a good effect. This study can predict movies' box office to reduce investment risk, so it is of great significance to movie investors and the social economy.