The semi-arid is a climate characterized by precipitation that is. insufficient to maintain crops and where evaporation often exceeds rainfall. Vegetation is one of the most sensitive indicators of environmental changes understanding the patterns of biodiversity distribution and what influences them is a fundamental pre-requisite for effective conservation and sustainable utilization of biodiversity. In this study. our focus was on examining the vegetation diversity in the semi-arid region of Tebessa. which falls within the Eastern Saharan Atlas domain in North Africa’s semi-arid zone. Plants were sampled at 15 sites distributed across the study area. The quadrat method was used to conduct floral surveys. The sampling area of each sample was 100 square meters 10 m × 10 m (quadrat). Each quadrat was measured for species richness (number of species). abundance (number of individuals). and Richness generic (plant cover). Based on the floristic research. 48 species were found. classified into 21 families. with Asteraceae accounting for 34.69% of the species and Poaceae accounting for 14.28%.

Private banking institutions serve the financial sector’s wealthiest clientele via a dedicated value proposition. Based on the relevant tendencies and statistics, a remarkable expansion can be outlined since the mid-1990s. The aim of this study is to elaborate the Hungarian private banking market’s development as a case study. The paper also intends to add to the literature on this unique segment of the financial market. Based on the available statistics, the analysis primarily focuses on the Hungarian private banking market’s rapid development process. This can be underpinned by the clientele’s savings, number of accounts and respective segmentation limits of the institutions. Referring to the amount of savings, a correlation analysis indicates significant co-movements with specific social and economic variables. The growth rate of the Hungarian clientele’s savings outperformed the respective indicator in Western Europe during the review time period (2007–2020). The current paper also includes a section that summarises general challenges that private banking managers need to address during the development process. Generally, the literature on private banking can still be considered scarce, whereas there is a lack of studies on the Central-Eastern European region. The analysis of the Hungarian sector’s development path can serve with relevant information to any financial expert in the field.

The present study focuses on improving Cognitive Radio Networks (CRNs) based on applying machine learning to spectrum sensing in remote learning scenarios. Remote education requires connection dependability and continuity that can be affected by the scarcity of the amount of usable spectrum and suboptimal spectrum usage. The solution for the proposed problem utilizes deep learning approaches, namely CNN and LSTM networks, to enhance the spectrum detection probability (92% detection accuracy) and consequently reduce the number of false alarms (5% false alarm rate) to maximize spectrum utilization efficiency. By developing the cooperative spectrum sensing where many users share their data, the system makes detection more reliable and energy-saving (achieving 92% energy efficiency) which is crucial for sustaining stable connections in educational scenarios. This approach addresses critical challenges in remote education by ensuring scalability across diverse network conditions and maintaining performance on resource-constrained devices like tablets and IoT sensors. Combining CRNs with new technologies like IoT and 5G improves their capabilities and allows these networks to meet the constantly changing loads of distant educational systems. This approach presents another prospect to spectrum management dilemmas in that education delivery needs are met optimally from any STI irrespective of the availability of resources in the locale. The results show that together with machine learning, CRNs can be considered a viable path to improving the networks' performance in the context of remote learning and advancing the future of education in the digital environment. This work also focuses on how machine learning has enabled the enhancement of CRNs for education and provides robust solutions that can meet the increasing needs of online learning.

The quality of preschool education is related to the stability of the early childhood teaching force. With the help of qualitative research methods, the study analyzed the data of eight teachers who left the profession and explored the process of teachers leaving the profession, and found that the encounter between "settling down" and "professional feelings", the struggle for transformation between "professional feelings" and "the situation", and the struggle for transformation between "settling down" and "the situation" are all related to the stability of the early childhood education workforce. It was found that the encounter and tug-of-war between "settling down" and "professional feelings", the struggle for transformation between "professional feelings" and "the situation", and the rational weighing between "settling down" and "the situation" are the important factors affecting the departure from the profession. The essence is the tension between "teachers as human beings" and "human beings as teachers". Therefore, it is necessary to pay attention to the unity of "person" and "teacher", and to alleviate the problem of teachers leaving the organization by creating a fair, democratic and professional working atmosphere and strengthening the awareness of professional education.

Madura Island, with more than half of its population, are women encountering socio-economic problems, which eventually create high poverty and unemployment rates. However, the Madurese are also well-known for their resiliency and entrepreneurial characteristics. The effort to solve the issues by empowering the community, women in particular, has been taken seriously primarily by entrepreneurs who were born and raised in the community. Therefore, this research aims to gain insight into the current Madurese entrepreneur’s business pattern and their social concerns in order to propose a strategy to increase productivity as an effort to empower women’s communities. The methodology is qualitative research, which collects data using semi-structured interviews with representatives of the Madurese entrepreneurs in four areas of Madura Island. Their responses are then transcripted and coded for content analysis based on the designed themes. The result shows that they recognise and practise the social entrepreneurship (SE) pattern, although they do not understand the term. Subsequently, the technological application for business operations in general is still limited to the usage of digital technology (DT) for marketing and transaction activities, which helps increase business performance or productivity. Hence, the initiation of technosociopreneurship as a strategy to further develop SE activities with the hope of increasing productivity in empowering women’s communities is proposed. Further research development is advised using quantitative methods for generalisable findings.