In the current context of multicultural collision, online information is impacting traditional gender values. To analyze the changes in gender role attitudes and gender awareness among Chinese Generation Z college students under the influence of various social factors, the study focuses on Generation Z college students and explores the impact of cultural, media, educational, and family factors on gender role attitudes and gender awareness among Chinese Generation Z college students through questionnaire surveys and quantitative analysis methods. The research results show that Generation Z college students exhibit extremely favorable gender perspectives, with the proportion of bisexual gender roles approaching 38%, surpassing the number of students with traditional understanding of single sex gender roles. At the same time, in school gender awareness education, research has found that the proportion of bisexual gender roles is the highest among students who accept open mindedness, at 46.6%. In family gender awareness education, students who receive parental gender awareness sharing education have the highest proportion of bisexual gender roles, accounting for 48.5%. Therefore, the current gender education for the new Generation of students in China needs to abandon traditional avoidance-based teaching methods and adopt an open and supportive attitude to guide students’ gender values.

Background and introduction: The East and Southeast Asian newly industrialized economies have shown spectacular economic development by their export-oriented development policies during recent decades, which resulted in not only economic wealth but enabled them to be technology exporters and investors. Their products, their flagship brands today are well-known and recognized throughout the world. It is not surprising that the Hungarian government—by its Hungarian Eastern Opening strategy—intended to focus on these economies, even though that with most of them there were intensive and broad co-operation in the fields of business, investment, culture, education and tourism. The new strategy gave a focus on increasing the diplomatic and trade relationship with the wider region, new embassies and trade representation offices were opened or re-opened in several locations with the view of intensifying the business and the people-to-people contacts. Even though the pandemic of Covid 19 and the energy crisis caused disruption in international trade, it can be said the trade and investment relations with these economies have still been growing, especially on the import side. The prospects of the growth of Hungarian exports to these destinations are modest which is hindered by the huge geographic distance, the peculiar consumer preferences, the merely different market conditions and the sharp competition. Objective: The aim of this paper to illustrate by statistical figures the state of the trade and investment relations between Hungary and the Republic of Korea, Taiwan, Singapore and Thailand. Methodology: Bibliographic and data analysis, focusing on the relevant international and Hungarian literature and databases, especially the trade and investment statistics of the Hungarian Central Statistical Office (HCSO/KSH).

Among contemporary computational techniques, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are favoured because of their capacity to tackle non-linear modelling and complex stochastic datasets. Nondeterministic models involve some computational intricacies when deciphering real-life problems but always yield better outcomes. For the first time, this study utilized the ANN and ANFIS models for modelling power generation/electric power output (EPO) from databases generated in a combined cycle power plant (CCPP). The study presents a comparative study between ANNs and ANFIS to estimate the power output generation of a combined cycle power plant in Turkey. The inputs of the ANN and ANFIS models are ambient temperature (AT), ambient pressure (AP), relative humidity (RH), and exhaust vacuum (V), correlated with electric power output. Several models were developed to achieve the best architecture as the number of hidden neurons varied for the ANNs, while the training process was conducted for the ANFIS model. A comparison of the developed hybrid models was completed using statistical criteria such as the coefficient of determination (R²), mean average error (MAE), and average absolute deviation (AAD). The R² of 0.945, MAE of 3.001%, and AAD of 3.722% for the ANN model were compared to those of R² of 0.9499, MAE of 2.843% and AAD of 2.842% for the ANFIS model. Even though both ANN and ANFIS are relevant in estimating and predicting power production, the ANFIS model exhibits higher superiority compared to the ANN model in accurately estimating the EPO of the CCPP located in Turkey and its environment.

The purpose of the study was to examine the role of personalization in motivating senior citizens to use AI driven fitness apps. Vroom’s expectancy theory of motivation was applied to examine the motivation of senior citizens. The responses from participants were collected through structured interviews. The participants belonged to South Asian origin belonging to India, Bangladesh, Nepal and Bhutan. The authors adopted a content analysis approach where the gathered interview responses were coded in the context of elements of Vroom’s theory. The findings of the study indicated that a highly personalized approach in the context of motivation, expectancy, instrumentality and valence will motivate senior citizens to use AI based fitness apps. The study contributes to the personalization of AI fitness apps for senior citizens.

This study aims to analyze the effect of financial literacy and financial education on digital financial inclusion in Mexico. The analysis is carried out with 13,554 data from the National Survey of Financial Inclusion 2021, corresponding to Mexican adults who use digital financial services. The population under study comprises people over 18 years old, residing in Mexico, disaggregated by size of locality, and divided into six geographical regions. The dichotomous Probit model is used to estimate the effect of financial literacy and sociodemographic variables on digital financial inclusion. The results show that financial literacy and financial education have a marginal effect, of 0.94% and 4.42%, respectively, on digital financial services. Results also show that the marginal effect of financial literacy and financial education is greater on the use of mobile payments than on the acquisition of online accounts or apps and online credit. The results also show that gender, locality size, educational level, income and asset holding have a statistically significant relationship with the use of digital financial services. The findings confirm that financial literacy and financial education contribute to the digital financial inclusion of Mexicans, in this sense, providing financial education can especially benefit vulnerable population groups such as those living in rural areas and those with low income and low education levels.

This study uses a Time-Varying Parameter Stochastic Volatility Vector Autoregression (TVP-SV-VAR) model to conduct an empirical analysis of the dynamic effects of China’s stock market volatility on the agricultural loan market and its channels. The results show that the relationship between stock market and agricultural loan market volatility is time varying and is always positive. The investor sentiment is a major conduit through which the effect takes place. This time-varying effect and transmission mechanism are most apparent between 2011 and 2017 and have since waned and stabilized. These have significant implications for the stable and orderly development of the agricultural loan market, highlighting the importance of the sound financial market system and timely policy, better market monitoring and early warning system and the formation of a mature and sound agricultural credit mechanism.

In the recent years, with global warming and the change in climatic characteristics, buildings and interior arrangements in dry and cold climates, that previously did not have cooling problems, now require built and pre-planned cooling systems as well as heating. On the other hand, the enormous increase in energy consumption and the rapid depletion of energy resources causes concern and anxiety for future generations. In this regard, utilizing natural resources and incorporating sustainable solutions into building design are critical. Vernacular technical systems and design ideas can still be accepted and applied to create sustainable solutions. In this context, design strategies for energy efficiency and provision of physical and spatial comforts could be considered based on traditional architecture. In this study, sustainable building design solutions that have been used in Iran’s vernacular houses, which has four distinct climate zones, aimed to create a paradigm for the general modern passive house designs in the global context. Traditional Iranian residential architecture incorporates architectural features for physical, spatial, and climatic needs, as well as aesthetic comfort for the user. In this manner, user needs and interior space organization in vernacular residential architecture can be considered as a sustainable housing model that meets today’s technology requirements in passive house design.