The goal of the project is to investigate and discover tree species abundant in the Mekong Delta Vietnam, and find out species to develop land in southern coastal of Vietnam and based on research to applicated for food and medicinal on part of forest trees. Mekong Delta a amount of alluvium sediments flows from upstream China to Vietnam by the river branches, then get out the Sea. This sediments accumulated gradually elevation the new land. The coastal where mangrove forests with a rich ecosystem of plants and animals. Over time, these forests change, with different plant species succeeding each other. This aims of this study to finding plant species, classification of forest types based on ecological regions, assessement the biodiversity of tree species, and compare the abundance communities, measuring the growth of the forest in these regions. In 2023, a comprehensive survey was conducted by using a systematic approach. Research content and methods. The content is to investigate the situation of woody plant species in mangrove forests in sub-regions with different ecological characteristics. The number of survey plots have done depend on the density of the forest, Base on the width of the forest range, the number of survey plots in sub region set up from 10 to 15 plots. In total, 68 plots have done established in the erea, the area of plot is 100 square meters (10 m x 10 m). Using the statistical software in forestry to survey and analysis data. The results of research is to find the number of species in each ecological region and growth situation, in which the important thing is to evaluate the adaptation of species in each sub-region to propose wich species to choose as the main species in aforestation the fastest land on sea. The result provided a complete picture of the tree species composition, distribution, and community structure characteristics in each ecological sub-region. The result of survey showed in the sub-region one is seven species. In the sub region two is eleven species. In the sub region three is eight species. In the region four is ten species. The total species of the mangrove forest in the Western Mekong Delta have 16 species from 11 plant families have been identified. Among these species have 6 dominant species include Avicennia oficinali),Avicennia alba, Rhizophora apiculata, Excoecaria agallocha, Someratia caseolaris, and Bruguiera yipamoriza. From the investigation have been found two species grow on the best on new land were Avicennia officinalis and Avicennia alba this findings show they can develope on the original new land for the shore of the Western Mekong Delta. The survey results also calculated the average of the height, diameter (D1.3), canopy, health of the nature mangrove tree for each sub region and total region. From these results showed the division of foresty structure, the structure of height, diameter (D1.3), canopy, heathy of the sub region and total region in the Western Mekong Delta. Suggestions after discovering during the investigation that there are Avicennia officinalis and Avicennia alba are two species that can implement development plants to expand natural land by planting on suitable sea surface areas for Mekong Delta of Vietnam. In addition, referring to research documents on these adapted species can exploit food and medicinal herbs in discovering the level biodiversity distribution abundance of these species. This finding can help Vietnam by mearsures using the species Aviecennia be discovered will promote sea reclamation faster instead of letting the natural law of sea reclamation follow.

This study examines the adoption and usability of lifestyle (LS) apps, considering demographic factors like age and education that influence adoption decisions. The study employed a mixed-methods design, combining an experiment (spanning 14 weeks of app use) with semi-structured interviews and periodic measurements. The researchers employed the Mobile Application Usability Questionnaire (MAUQ) to identify pivotal aspects of standalone app usability, interface satisfaction, and usefulness at various stages of use, with a particular emphasis on the experiences of Hungarian students (n = 36). The results demonstrate that health-related factors have a significant impact on students’ behavior and evaluation of lifestyle apps over the 14-week period. Overall, the analyzed LS apps demonstrated positive outcomes in terms of supporting subject health and significantly improving the perceived health state. The findings highlight both practical and theoretical contributions to the field of mobile health applications, suggesting avenues for further research to either confirm or challenge existing theories.

Under the background of economic globalization and the rapid development of science and technology, the development of higher education (HE) has undergone profound changes. Nowadays, in order to increase the international competitiveness, training international talents has become the primary task of universities and HE institutions. Therefore, taking Shenzhen as an example, the research takes quantitative method to study how the educational resources in the society affect the school from a macro perspective, and the micro perspective of students, teachers and schools, studying the impact on the development of universities. Through in-depth analysis of the integration of educational resources, the results show that multilingual library resource, and other three factors followed, are critical factors in the development of HE. And then, this study puts forward corresponding countermeasures and suggestions after discussion, aiming to provide strategic insights to enhance the quality and international competitiveness of HE in the GBA, especially in the construction of multilingual library resources (MLR), international exchange platform (IEP), sufficient and diverse laboratory facilities (SDLF), and rich academic resources (RAR). Thus, the research narrows the gap in this field to some extent.

A comprehensive survey was conducted in 2012 and 2020 to assess the financial culture of Hungarian higher education students. The findings revealed that financial training effectiveness had not improved over time. To address this, a conative examination of financial personality was initiated by the Financial Compass Foundation, which gathered over 40,000 responses from three distinct age groups: Children, high school students, and adults. The study identified key behavioral patterns, such as excessive spending and financial fragility, which were prominent across all age groups. These results informed Hungary’s seven-year strategy to enhance financial literacy and integrate economic education into the National Core Curriculum. The research is now expanding internationally with the aim of building a comparative database. The study’s main findings highlight the widespread need for improved financial education, with more than 80% of adults demonstrating risky financial behaviors. The implications of these findings suggest the importance of early financial education and tailored interventions to foster long-term financial stability. The international expansion of this research will allow for the examination of country-specific financial behaviors and provide data-driven recommendations for policy development.

With the advent of the big data era, the amount of various types of data is growing exponentially. Technologies such as big data, cloud computing, and artificial intelligence have achieved unprecedented development speed, and countries, regions, and multiple fields have included big data technology in their key development strategies. Big data technology has been widely applied in various aspects of society and has achieved significant results. Using data to speak, analyze, manage, make decisions, and innovate has become the development direction of various fields in society. Taxation is the main form of China’s fiscal revenue, playing an important role in improving the national economic structure and regulating income distribution, and is the fundamental guarantee for promoting social development. Re examining the tax administration of tax authorities in the context of big data can achieve efficient and reasonable application of big data technology in tax administration, and better serve tax administration. Big data technology has the characteristics of scale, diversity, and speed. The effect of tax big data on tax collection and management is becoming increasingly prominent, gradually forming a new tax collection and management system driven by tax big data. The key research content of this article is how to organically combine big data technology with tax management, how to fully leverage the advantages of big data, and how to solve the problems of insufficient application of big data technology, lack of data security guarantee, and shortage of big data application talents in tax authorities when applying big data to tax management.