Buru Regency is the primary hub for producing eucalyptus oil, a highly valued commodity in the region. The oil extracted from the eucalyptus epidemic plant possesses antiseptic, antibacterial, and antifungal characteristics. Amidst the Covid-19 pandemic, numerous industries require it as a fundamental component of pharmaceuticals. An essential factor in the eucalyptus oil production process is the presence of eucalyptus leaves. Therefore, leaf-sorting workers, including women, are required to ensure this availability. However, in reality, the daily lives of eucalyptus leaf massagers are characterized by challenging economic conditions and a socio-economic environment that lags behind workers in other sectors. This study aims to examine and investigate the roles and work patterns of employed women and the strategies they employ to ensure the consistent flow of household income. The research employed a qualitative methodology with a phenomenological approach. A total of 24 informants were purposefully selected based on their involvement in achieving the research objectives. The results indicate that the COVID-19 pandemic has altered the circumstances of women who collect leaves and rely heavily on eucalyptus trees as a natural resource. Physical adaptation strategies are the preferred methods used to fulfill household requirements. Implementing physical adaptations does not deter women leaf-sorters from continuing their work. Their commitment to meeting their basic needs significantly motivates them to persist in their role as leaf sorters. The income of women engaged in sorting eucalyptus leaves in their households during the COVID-19 pandemic.

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 systemically examines the numerous impacts of climate change on agriculture in Tunisia. In this study, we establish an empirical and comprehensive methodology to assess the effects of climate changes on Tunisian agriculture by investigating current climatic patterns using crop yields and socioeconomic variables. The study also assesses the types of adaptation strategies agriculture uses in Tunisia and explores their effectiveness in coping with climate-related adversities. We also consider some resilience factors, namely the ecological aspect and economic and social camouflage pursued by the (very) men in Tunisian agriculture. We also extensively discuss the complex interconnected relationship between policy interventions and community-based adaptations, a crucial part of the ongoing debate on climate change adaptation and resilience in agriculture. The findings of this study contribute to this important conversation, particularly for areas facing similar challenges.

Freshwater problems in coastal areas include the process of salt intrusion which occurs due to decreasing groundwater levels below sea level which can cause an increase in salt levels in groundwater so that the water cannot be used for water purposes, human consumption and agricultural needs. The main objective of this research is to implementation of RWH to fulfill clean water needs in tropical coastal area in Tanah Merah Village, Indragiri Hilir Regency, with the aim of providing clean water to coastal communities. The approach method used based on fuzzy logic (FL). The model input data includes the effective area of the house’s roof, annual rainfall, roof runoff coefficient, and water consumption based on the number of families. The BWS III Sumatera provided the rainfall data for this research, which was collected from the Keritang rainfall monitoring station during 2015 and 2021. The research findings show that FL based on household scale RWH technology is used to supply clean water in tropical coastal areas that the largest rainwater contribution for the 144 m² house type for the number of residents in a house of four people with a tank capacity of 29 m² is 99.45%.

One of the most important ways to achieve the goals stipulated by the Paris (2015) Agree-ment on climate change is to solve a two-fold task: 1) the adsorption of CO2 by the forest communities fcom the atmosphere during global warming and 2) their adaptation to these climate changes, which should ensure the effectiveness of adsorption itself. Report presents the regional experience of the numerical solution of this task. Calculations of the carbon balance of forests in the Oka-Volga River basin were carried out for global forecasts of moderate and extreme warming. The proposed index of labile elastic-plastic stability of forest ecosystems, which characterizes their succession-restorative po-tential, was used as an indicator of adaptation. A numerical experiment was conducted to assess the effect of the elastic-plastic stability of forest formations and the predicted climatic conditions on the carbon balance. In the upcoming 100-year forecast period, the overall stability of forest formations should increase, and to the greatest extent with extreme warming. Accordingly, one should expect a significant increase in the ability of boreal forests to ab-sorb greenhouse gases. It is determined unambiguous picture of a significant increase in the adsorption capacity of boreal forests with a rise in their regenerative potential.