Fire hazard is often mapped as a static conditional probability of fire characteristics’ occurrence. We developed a dynamic product for operational risk management to forecast the probability of occurrence of fire radiative power in the locally possible near-maximum fire intensity range. We applied standard machine learning techniques to remotely sensed data. We used a block maxima approach to sample the most extreme fire radiative power (FRP) MODIS retrievals in free-burning fuels for each fire season between 2001 and 2020 and associated weather, fuel, and topography features in northwestern south America. We used the random forest algorithm for both classification and regression, implementing the backward stepwise repression procedure. We solved the classification problem predicting the probability of occurrence of near-maximum wildfire intensity with 75% recall out-of-sample in ten annual test sets running time series cross validation, and 77% recall and 85% ROC-AUC out-of-sample in a twenty-fold cross-validation to gauge a realistic expectation of model performance in production. We solved the regression problem predicting FRP with 86% r² in-sample, but out-of-sample performance was unsatisfactory. Our model predicts well fatal and near-fatal incidents reported in Peru and Colombia out-of-sample in mountainous areas and unimodal fire regimes, the signal decays in bimodal fire regimes.

Water scarcity, particularly in arid and semi-arid regions, is a critical issue affecting forest management. This study investigates the effects of drought stress on the water requirement and morphological characteristics of two important tree species Turkish pine and Chinaberry. Using a factorial design, the study examines the impact of three age stages (one-year-old, three-year-old, and five-year-old plants) and three levels of drought stress on these species. Microlysimeters of varying sizes were employed to simulate different drought conditions. Soil moisture was monitored to show the effect of the various irrigation schedules. The study also calculated reference crop evapotranspiration (ET₀) using the PMF-56 method and developed plant coefficients (Kc) for the species. Results showed that evapotranspiration increased with soil moisture, peaking during summer and decreasing in winter. Turkish pine exhibited higher plant ET than Chinaberry, particularly among one-year-old seedlings. Drought stress significantly reduced evapotranspiration and water uses for both species, highlighting the importance of efficient water management in afforestation projects. The findings underscore the necessity of selecting drought-resistant species and optimizing irrigation practices to enhance the sustainability of green spaces in arid regions. These insights are crucial for improving urban forestry management and mitigating the impacts of water scarcity in Iran and similar climates globally.

Due to rising global environmental challenges, air/water pollution treatment technologies, especially membrane techniques, have been focused on. In this context, air or purification membranes have been considered effective for environmental remediation. In the field of polymeric membranes, high-performance polymer/graphene nanocomposite membranes have gained increasing research attention. The polymer/graphene nanomaterials exposed several potential benefits when processed as membranes. This review explains the utilization of polymer and graphene-derived nanocomposites towards membrane formation and water or gas separation or decontamination properties. Here, different membrane designs have been developed depending upon the polymer types (poly(vinyl alcohol), poly(vinyl chloride), poly(dimethyl siloxane), polysulfone, poly(methyl methacrylate), etc.) and graphene functionalities. Including graphene in polymers influences membrane microstructure, physical features, molecular permeability or selectivity, and separations. Polysulfone/graphene oxide nanocomposite membranes have been found to be most efficient with an enhanced rejection rate of 90%–95%, a high water flux >180 L/m²/h, and a desirable water contact angle for water purification purposes. For gas separation membranes, efficient membranes have been reported as polysulfone/graphene oxide and poly(dimethyl siloxane)/graphene oxide nanocomposites. In these membranes, N₂, CO₂, and other gases permeability has been found to be higher than even >99.9%. Similarly, higher selectivity values for gases like CO₂/CH₄ have been observed. Thus, high-performance graphene-based nanocomposite membranes possess high potential to overcome the challenges related to water or gas molecular separations.

The study’s purpose is to evaluate the influence of some factors of the model of planned behavior (TPB) and the perceived academic support of the university on the attitude toward entrepreneurship and entrepreneurial intention of students. The results of Structural Equation Modeling (SEM) linear structural model analysis with primary data collected from 1162 students indicated that entrepreneurial intention is influenced by attitude toward entrepreneurship, subjective norm, perceived educational support, and perceived concept development support. In addition, this study also found the positive influence of perceived educational support, concept development support, and business development support on attitude towards entrepreneurship. Interestingly, the influence of perceived business development support on entrepreneurial intention was rejected, and personal innovativeness is demonstrated to promote an attitude toward entrepreneurship. Notably, this study also highlights the moderating role of personal innovativeness on the relationship between attitude toward entrepreneurship and entrepreneurial intention. Based on these findings, several implications were suggested to researchers, universities, and policymakers.

Luxembourg institutions have the opportunity to reconcile environmental goals with financial stability by implementing Green Fintech solutions, as the banking sector increasingly recognizes the importance of sustainability. This study employs a quantitative approach and analyzes data collected from 150 participants working in the banking industry of Luxembourg. The research aims to assess the consequences of adopting Green Fintech on sustainable development. Banking institutions can boost their financial resilience and mitigate climate-related risks by adopting Green Fintech, which improves their sustainability. The paper emphasizes the importance of Green Fintech in the Luxembourg banking sector for advancing sustainable development goals. To effectively address the increasingly complex environmental concerns, it is crucial to embrace innovative Fintechs.

Adequate sanitation is crucial for human health and well-being, yet billions worldwide lack access to basic facilities. This comprehensive review examines the emerging field of intelligent sanitation systems, which leverage Internet of Things (IoT) and advanced Artificial Intelligence (AI) technologies to address global sanitation challenges. The existing intelligent sanitation systems and applications is still in their early stages, marked by inconsistencies and gaps. The paper consolidates fragmented research from both academic and industrial perspectives based on PRISMA protocol, exploring the historical development, current state, and future potential of intelligent sanitation solutions. The assessment of existing intelligent sanitation systems focuses on system detection, health monitoring, and AI enhancement. The paper examines how IoT-enabled data collection and AI-driven analytics can optimize sanitation facility performance, predict system failures, detect health risks, and inform decision-making for sanitation improvements. By synthesizing existing research, identifying knowledge gaps, and discussing opportunities and challenges, this review provides valuable insights for practitioners, academics, engineers, policymakers, and other stakeholders. It offers a foundation for understanding how advanced IoT and AI techniques can enhance the efficiency, sustainability, and safety of the sanitation industry.