The Mediterranean region is regarded as a hot spot on Earth because of its placement at the junction of many aerosols. Numerous studies have demonstrated that the North Atlantic Oscillation (NAO), which is closely related to the El Niño–Southern Oscillation (ENSO) phenomenon, influences the weather in the area. However, a recent study by the same author examined the ENSO effect on atmospheric processes in this area and discovered a slight but notable influence. This study builds on that earlier work, but it divides the Mediterranean region into four smaller regions during the same time span as the previous study, which is extended by two years, from 1980 to 2024. The division is based on geographical, climatological, and atmospheric process features. The findings demonstrate that volcanic eruptions significantly affect the total amount of aerosols. Additionally, the current study reveals that the Granger-causality test of the physical phenomena of solar activity, ENSO, and NAO indicates that all have a significant impact, either separately or in combination, on the atmospheric process over the four Mediterranean regions, and this effect can last up to six months. Moreover, a taxonomy of the different forms of aerosols across the four subregions is given.
Soil erosion threatens mixed farms in marginal areas, endangering their cultural and economic role in territories where pastoralist systems are already under pressure for climatic, socioeconomic, and generational factors. The rise in extreme rainfall events worsens soil loss on farmland, underscoring the need to co-develop practices that boost climate resilience in agriculture. This study helps fill the gap in understanding how the integration of farmers' perceptions with spatial modeling can inform land management strategies. We combined farmers' perceptions, model predictions, and farm management to provide an integrated assessment of the soil erosion. We represented the geographical distribution of soil erosion risk through geographical information systems-based RUSLE modeling. Farmers' perceptions on soil erosion were assessed through surveys and fuzzy cognitive mapping conducted across 25 sheep farms. Our model shows that 37% of cropland is at risk, mainly due to land topography and soil cover. Fuzzy cognitive maps reveal that farmers are aware of the main environmental and human-linked soil erosion drivers. Farmers recognize cropping system design, especially using perennial forage instead of annual crops, as key to reducing soil erosion, and also see temporary ditches, reduced tillage, and agroforestry as effective measures. Utilizing a multivariate ordinal logistic regression, we showed that sheep farmers with a higher education level tend to perceive higher soil erosion risk. The number of conservation measures adopted increases when farmers are more aware of soil erosion issues, when they identify a higher number of fuzzy cognitive map connections, and when the predicted soil erosion risk is higher. Farmers' perceptions of erosion risks and soil conservation measures aligned with model predictions on soil erosion, highlighting the importance of systematically involving farmers in research and policy design. Their detailed mental models enhance environmental models and should be considered in the European Common Agricultural Policy for sustainable rural development.
Ongoing food system inequalities and pressures on planetary boundaries requires a paradigm shift among agricultural research for development (AR4D) actors to produce effective innovation for sustainable environmental and social outcomes. Building on insights from Agricultural Innovation System literature and recognizing the influence of personal and systemic biases within AR4D, the following recommendations address upstream challenges, interdisciplinary collaboration, emphasize outcome-driven scaling, adaptive project implementation, and integrate critical considerations for social differentiation.
Recent advances in artificial intelligence (AI) have generated widespread interest and investment across industries, yet the environmental and public health costs of large-scale model training remain poorly understood [...]
It has been witnessed that post-COVID there has been a rapid expansion of online education, that has heightened the need to understand learner engagement and its influence on course completion, especially in a mobile-first digital landscape. This is a data-driven study that explores key engagement metrics such as time spent on courses, number of videos watched, quizzes taken, and quiz scores to evaluate their impact on the completion rates of online courses. The dataset has been referred from health, arts, science, and programming for over 5,000 user records. This study investigates how behavioral patterns and device types, particularly mobile phone usage, affect learner success. The study employs descriptive and comparative analytics to measure the relationships between engagement indicators and completion outcomes. Variables like course category, time spent on course, and device type are analyzed alongside performance metrics such as completion rate and quiz scores. The findings show that higher engagement through interactive content, especially video consumption and quiz participation, is significantly associated with improved completion rates. Learners accessing courses via mobile devices exhibited distinct engagement behaviors that suggest the importance of mobile-optimized learning strategies. This study is applied in a global context, and we have applied publicly available anonymized data to analyze results and offer actionable insights for educational platforms, instructional designers, and policymakers aiming to enhance learner retention and success in online learning environments.
