In the contemporary landscape characterized by technological advancements and a progressive economic environment, the utilization of currency has undergone a paradigm shift. Despite the growing prevalence of digital currency, its adoption among the Vietnamese population faces several challenges, including limited financial literacy, concerns over security, and resistance to change from traditional cash-based transactions. This research aims to identify these challenges and propose solutions to encourage the widespread use of digital currency in Vietnam. This research adopts a quantitative approach, utilizing Likert scale questionnaires, with a dataset of 330 records. The interrelationships among variables are analyzed using partial least squares structural equation modeling (PLS-SEM). The analysis results substantiate the viability of the research model, confirming the hypotheses. The findings demonstrate a positive relationship and the significance impact of factors such as perceived usefulness (PU), perceived ease of use (PEOU), perceived trust (PT), social influence (SI), openness to innovation (OI), and financial knowledge (FK) to intention to use digital currency (IUDC). Thereby aiming to inform policymakers, industry stakeholders, and the wider community, fostering a deeper understanding of consumer behavior and providing solutions to enhance the adoption of digital currency in the evolving landscape of digital finance.

This study examines aggressive behavior among adolescents in school settings, focusing on its associations with mental health dimensions such as dysfunctional negative emotions and anxiety. A total of 403 adolescents (234 girls and 169 boys) aged 12 and 13 years participated in the study. Self-report questionnaires assessed aggressive tendencies and mental health symptoms, while demographic variables such as age and gender were also collected. Data analysis revealed a non-normal distribution, as determined by the Kolmogorov-Smirnov and Shapiro-Wilk tests. Consequently, non-parametric statistical methods were employed, including the Spearman correlation coefficient to explore relationships between variables and the Mann-Whitney U test to analyze gender differences. The results demonstrated significant positive correlations between aggressive behavior and dysfunctional negative emotions (r = 0.191, p < 0.01) and between aggression and anxiety (r = 0.275, p < 0.01). Additionally, gender differences emerged, with females reporting higher levels of mental health symptoms than males (p < 0.05). These findings highlight the complex relationship between mental health challenges and aggression, emphasizing the significant roles of gender and emotional regulation in shaping these dynamics. The study calls for the development of tailored psychological interventions that not only address aggressive behaviors but also consider the unique mental health needs and emotional profiles of adolescents, ensuring a more personalized and effective approach to support their well-being.

Using generative artificial intelligence systems in the classroom for law case analysis teaching can enhance the efficiency and accuracy of knowledge delivery. They can create interactive learning environments that are appropriate, immersive, integrated, and evocative, guiding students to conduct case analysis from interdisciplinary and cross-cultural perspectives. This teaching method not only increases students’ interest and participation in learning but also helps cultivate their interdisciplinary thinking and global vision. However, the application of generative artificial intelligence systems in legal education also faces some challenges and issues. If students excessively rely on these systems, their ability to think independently, make judgments, and innovate may be weakened, leading to over-trust in machines and reinforcement of value biases. To address these challenges and issues, legal education should focus more on cultivating students’ questioning skills, self-analysis abilities, critical thinking, basic legal literacy, digital skills, and humanistic spirit. This will enable students to respond to the challenges brought by generative artificial intelligence and ensure their comprehensive development in the new era.

The process management variable and the service quality variable date most prominently from the beginning of the last century, and therefore, in organizations from different parts of the world, whose search was to contribute effectively to administrative tasks, facing the challenges of constant changes and evaluations. In Peru, both variables were implemented since 2018, by technical standards, in order to contribute and improve public institutional work. Thus, the objective was to know the most outstanding characteristics of process management and service quality, using studies from different entities at the ecumenical level and revealing their main benefits of application and contribution. Furthermore, based on the systematic and methodical review of scientific articles from databases indexed to multiple journals, which are registered and organized in databases such as WOS and SCOPUS, thus theorizing their authors and perspectives. For this study, the documentary analysis technique and the data collection guide were considered as an instrument; in accordance with the PRISMA method. Finally, it is concluded that process management are methods available in an organization to provide effective results using resources efficiently, with dimensions of analysis, monitoring, and process improvements, contributing to organizational and strategic productivity; Likewise, the quality of the service is user satisfaction when judging the value of some service, dimensioning, analyzing needs, as well as evaluating, supervising and improving the service, fulfilling needs with knowledge of their expectations.

Liquid Metal Battery (LMB) technology is a new research area born from a different economic and political climate that has the ability to address the deficiencies of a society where electrical energy storage alternatives are lacking. The United States government has begun to fund scholarly research work at its top industrial and national laboratories. This was to develop Liquid Metal Battery cells for energy storage solutions. This research was encouraged during the Cold War battle for scientific superiority. Intensive research then drifted towards high-energy rechargeable batteries, which work better for automobiles and other applications. Intensive research has been carried out on the development of electrochemical rechargeable all-liquid energy storage batteries. The recent request for green energy transfer and storage for various applications, ranging from small-scale to large-scale power storage, has increased energy storage advancements and explorations. The criteria of high energy density, low cost, and extensive energy storage provision have been met through lithium-ion batteries, sodium-ion batteries, and Liquid Metal Battery development. The objective of this research is to establish that Liquid Metal Battery technology could provide research concepts that give projections of the probable electrode metals that could be harnessed for LMB development. Thus, at the end of this research, it was discovered that the parameter estimation of the Li//Cd-Sb combination is most viable for LMB production when compared with Li//Cd-Bi, Li-Bi, and Li-Cd constituents. This unique constituent of the LMB parameter estimation would yield a better outcome for LMB development.

Drawing on the theoretical framework of Job Demands-Resources (JD-R), our study aims to consider how workplace antecedents of perceived quiet firing (also known as involuntary attrition), perceived co-worker support, and experience (tenure at an organization) may influence quiet quitting behavior. Data were collected via questionnaire responses from 209 workers in India who had graduated from university within the last 7 years. The findings show that (1) perceived quiet firing is positively associated with quiet quitting; (2) perceived co-worker support is negatively associated with quiet quitting; (3) experience moderates the positive association between perceived quiet firing and quiet quitting in such a way that the relationship is weaker as one’s tenure at an organization increases; and (4) experience does not moderate the negative association between perceived co-worker support and quiet quitting. The study’s contributions come from understanding how the interplay of demands (i.e., perceived quiet firing) and resources (i.e., perceived co-worker support and experience) determine quiet quitting behaviors in the workplace. Additionally, the temporal dimension of experience facilitates the acquisition of organizational-specific knowledge and resources. In contrast, perceptions of co-worker support appear specific to a given point in time. Policy implications come from providing guidance to organizations on how to reduce quiet quitting behaviors by ensuring that the resources available to employees exceed the demands placed on them.