The affectations caused by extreme events of natural origin such as droughts and floods in traditional homes in the province of Gran Chaco, in Bolivia, are frequent. These aspects compromise the habitat of the populations that occupy them, as is the case of the original Weenhayek people, as an alternative for the improvement of the human habitat of this town. Through theoretical and empirical methods, five variables used for the development of the adaptation model were determined, from the bases of planned adaptation as a component of urban-territorial resilience, in search of an improvement of socio-environmental systems in the face of the effects of climate change, exemplified in the Weenhayek native people. The model establishes the improvements of traditional dwellings, from a current trend of deterioration to one of preservation, conservation and growth in the Weenhayek culture, through various features, such as: Respects the cultural design of the house that integrates local patterns of the environment, ecosystem and contemporary construction elements without affecting its image, the materials and construction techniques used are of a traditional nature, but with contemporary elements that improve their application, durability, stability, as an articulated construction system, commits governments in all instances to the technical-constructive study of the rural areas of the human settlements of the Weenhayek people, and establishes a starting point towards new studies focused on native peoples.

The study’s goal was to investigate the impact of e-learning determinants on student satisfaction and intention to use e-learning tools. The dependent and independent variables in this study were based on the technological acceptance model. The study examines three determinants, including usefulness, ease of use, and facilitating conditions, as independent variables, while student satisfaction and intention to use were used as dependent variables. Additionally, this study is unique by adding student satisfaction as a dependent variable and a mediator to examine the relationship between e-learning determinants and intention to use. A questionnaire was prepared and distributed to 324 undergraduate students from Jordan’s private universities on the basis of a convenience sample. The proposed hypotheses were investigated using the quantitative techniques of regression in SPSS and SEM in AMOS. The findings of this study revealed that student satisfaction and intention to use e-learning were positively impacted by e-learning determinants. It found that intention to use was positively impacted by student satisfaction. Furthermore, e-learning intention to use was found to be positively impacted by e-learning determinants via student satisfaction. Universities and other educational institutions are advised to identify the appropriate e-learning determinants that satisfy students’ demands and motivate them to use e-learning tools in light of the study’s findings. Private universities can accomplish their goals, stay ahead of the competition, and obtain a competitive advantage by properly understanding e-learning determinants, student satisfaction, and the application of successful e-learning solutions.

This paper concerns a miniature gasifier fed with a constant ambient-pressure flow of air to study the pyrolysis and subsequent combustion stage of a single wood pellet at T = 800 ℃. The alkali release and the concentration of simple gases were recorded simultaneously using an improved alkali surface ionisation detector and a mass spectrometer in time steps of 1 s and 1.2 s, respectively. It showed alkali release during both stages. During combustion, the MS data showed almost complete oxidation of the charred pellet to CO₂. The derived alkali release, “O₂ consumed”, and “CO₂ produced” conversion rates all indicated very similar temporal growth and coalescence features with respect to the varying char pore surface area underlying the original random pore model of Bhatia and Perlmutter. But, also large, rapid signal accelerations near the end and marked peak-tails with O₂ and CO₂ after that, but not with the alkali release data. The latter features appear indicative of alkali–deprived char attributable to the preceding pyrolysis with flowing air. Except for the peak-tails, all other features were reproduced well with the modified model equations of Struis et al. and the parameter values resembled closely those reported for fir charcoal gasified with CO₂ at T = 800 ℃.

Urban regeneration and gentrification are complex, interconnected processes that significantly shape cities. However, these phenomena in the Middle East and North Africa (MENA) region are often understudied and typically viewed through a Western lens. This systematic review of literature from 2010 to 2024 addresses this gap by synthesizing a comprehensive framework for understanding urban regeneration-led gentrification in MENA countries. The review delves into key themes: Gentrification contexts, the regeneration process, gentrification accelerators, and the aftermath of gentrification. It explores the diverse motives behind urban regeneration, identifies key stakeholders, and analyzes catalysts of gentrification. Findings reveal that informal areas and deteriorated heritage sites in major cities are most susceptible to gentrification. The study also highlights the critical issue of insufficient community participation and proposes a participation evaluation framework. The unique socioeconomic and political factors driving gentrification in the MENA region underscore the necessity of context-specific approaches, facilitating the identification of regional similarities and differences. Conclusively, the review asserts that gentrification is a cyclic process, necessitating core interventions through enhanced regeneration strategies or displacement plans to mitigate its effects.

This study conducted a systematic literature review on current and emerging trends in the use of artificial intelligence (AI) for community surveillance, using the PRISMA methodology and the paifal.ai tool for the selection and analysis of relevant sources. Five main thematic areas were identified: AI technologies, specific applications, societal impact, regulations and public policy. Our findings revealed exponential growth in the development and implementation of AI technologies, with applications ranging from public safety to environmental monitoring. However, this advancement poses significant challenges related to privacy, ethics and governance, driving a debate on the need for appropriate regulations. The analysis also highlighted the disparity in the adoption of these technologies among different communities, suggesting a need for inclusive policies to ensure equitable benefits. This study contributes to the understanding of the current scenario of AI in community policing, providing a solid foundation for future research and developments in the field.