Nowadays, more and more cars have begun to enter into innumerable families; the family car has become a necessity for Chinese households who have certain purchasing power. However, the ups and downs of oil prices have brought some impact on people's automobile consumption activities. Therefore, after collecting the information of the oil price and family car consumer, carried on through in-depth analysis of the relevant data with reasonable relationship, and then developed a suitable for China's national conditions and finished oil pricing model, thereby the National Development and Reform Commission have proposed the suggestion for China's refined oil pricing mechanisms and promoting the healthy development of new energy vehicles with specific measures. For question 1, through the problem analysis and information access, combined with the past and current situation of the domestic refined oil prices, we analyze the following seven factors: international crude oil prices, China's annual crude oil imports, China's annual crude oil exports, crude oil output in China, China's annual GDP per capita, China's annual consumption of crude oil, the total annual energy consumption in China, all have influence on China's refined oil prices. By monadic linear regression analysis, annual average prices of domestic refined oil products have a certain correlation with the various influencing factors, and then by multiple linear regression way eventually concluded the final relationship between oil prices and the influence factors, which compared with the current price, and make reasonable evaluation model. Through the establishment of various influencing factors and function of time, and using the evaluation model for refined oil product price to make reasonable forecast. According to this model, in order to predict refined oil product price as $122.15 per barrel in 2016. For question two, we basically sums up three key factor which influence the quantity of family vehicle: China's oil product prices, the annual GDP per capita, total road mileage. Through Excel to make the relationship curves of different quantity of family cars against influencing factors, and use Grey Forecasting method to forecast the quantity of family cars. And carries on the residual error test, it is used to conclude that the rationality of the model is highly. The number of private cars of the city of xi 'an is predicts that to 8.302 million vehicles by 2020. For question three, we discussed the relationship between international crude oil prices and domestic exports of crude oil export with domestic refined oil prices, through its multiple linear regressions to get the final pricing model. For question four, according to three previous established models, we proposed China's refined oil pricing mechanism proposal to the national development and Reform Commission: perfect price controls, deeper product market, and integration of resources consideration and environmental protection class tax types, adjust the consumption tax collection and Administration links, and improve the production cost accounting.

With the development of material life, the importance of plants in life has become increasingly prominent, and indoor flowers are also popular. As we all know, plants have purified air, refreshing brainwashing, promote sleep, sterilization and other effects, such as mint, Clivia, aloe and so on. Therefore, the choice of plants corresponding to their own needs is particularly important, while to note that some flowers should not be placed indoors. And different flowers on the water, temperature, light, soil and other requirements are not the same.

Using a newly developed data set, we analyze the effects of infrastructure investment on economic performance in Portugal. A vector-autoregressive approach estimates the elasticity and marginal products of twelve types of infrastructure investment on private investment, employment, and output. We find that the largest long-term accumulated effects come from investments in railroads, ports, airports, health, education, and telecommunications. For these infrastructures, the output multipliers suggest that these investments pay for themselves through additional tax revenues. For investments in ports, airports and education infrastructures, the bulk of the effects are short-term demand-side effects, while for railroads, health, and telecommunications, the impact is mostly of a long-term and supply-side nature. Finally, investments in health and airports exhibit decreasing marginal returns, with railroads, ports, and telecommunications being relatively stable. In terms of the other infrastructure assets, the economic effects of investments in municipal roads, electricity and gas, and refineries are insignificant, while investments in national roads, highways, and waste and waste water have positive economic effects but too small to improve the public budget. Clearly, from a policy perspective, not all infrastructure investments in Portugal are created equal.

With the deep integration of artificial intelligence technology in education, the development of AI integration capabilities among pre-service teachers—as the core of future educational human resources—has become crucial for enhancing educational quality and driving digital transformation in education. Based on the AI-TPACK (Artificial Intelligence-Technological Pedagogical Content Knowledge) theoretical framework, this study employs questionnaire surveys and structural equation modeling to explore the structural characteristics, influencing factors, and formation mechanisms of AI-TPACK competencies among pre-service teachers in Chinese universities. Findings indicate that while pre-service teachers demonstrate moderately high overall AI-TPACK levels, their technical knowledge (AI-TK) and technological integration competencies (e.g., AI-TPK, AI-TCK) remain relatively weak. School technical support, technological attitudes, and technological competence significantly influence their AI-TPACK capabilities, with institutional level and teaching experience serving as important external moderating factors. Building on these findings, this paper proposes a systematic framework for developing pre-service teachers' AI integration capabilities from a human resource development perspective. This framework encompasses four dimensions: curriculum optimization, practice enhancement, resource support, and policy guidance. It aims to provide theoretical foundations and practical pathways for pre-service teacher training and teacher human resource development in higher education institutions.

This study examines how the framing of organizational gender-equity policies shapes support among Generation Z employees. Drawing on performativity (Butler, 1990) and intersectionality (Crenshaw, 1991), we conceptualize framing as mediating how Gen Z employees perceive equity initiatives. Using a mixed-methods design, we combine survey data from 4,861 Gen Z respondents in 30 countries with directed content analysis of four HR policy documents (coded for equity vs enforcement, identity recognition, and youth engagement). Results reveal a gender gap: Gen Z women strongly endorse inclusive equity measures, consistent with evidence that women show stronger support for equality policies, whereas Gen Z men are more skeptical of policies framed as exclusive or punitive – mirroring polls finding many Gen Z men say equality efforts have gone too far. These findings suggest that performative policy framing activates social identities differently by gender and that intersectional policy language affects reception. Practically, we recommend framing equity initiatives in terms of shared fairness and collective benefit, using transparent rationale and inclusive identity language. Gen Zers expect fair pay, inclusive policies, and transparency, so HR communications should emphasize fairness and allyship to enhance legitimacy and support among this cohort.