In Chile, as in many other areas of the world, water supplies have been poorly managed and water availability is decreasing. In order to manage water resources more sustainably and equitably, it is necessary to understand and predict their supply and use considering the characteristics of a particular zone. This study aimed to develop a conceptual model for water management in the Libertador Bernardo O’Higgins Region in Chile. The model considers the water needs of industries with production activities, human consumption, and the ecological flow of each sub-basin in the area. The results show that the proposed model contributes to the understanding of the critical variables, their agents, and the interaction between the hydric demands, which enables the prioritization of human consumption and the ecological flow. Furthermore, the cross-analysis between the offer and demand indicates that current and predicted consumption levels will only be sustainable up to the year 2031. The findings may be of use to decision-makers seeking to improve water management plans in this area and elsewhere, and to others interested in modeling water management in different areas.

Fighting the COVID-19 pandemic, most countries have implemented non-pharmaceutical interventions like wearing masks, physical distancing, lockdown, and travel restrictions. Because of their economic and logistical effects, tracking mobility changes during quarantines is crucial in assessing their efficacy and predicting the virus spread. Unlike many other heavily affected countries, Chile implemented quarantines at a more localized level, shutting down small administrative zones, rather than the whole country or large regions. Given the non-obvious effects of these localized quarantines, tracking mobility becomes even more critical in Chile. To assess the impact on human mobility of the localized quarantines, we analyze a mobile phone dataset made available by Telefónica Chile, which comprises 31 billion eXtended Detail Records and 5.4 million users covering the period February 26th to September 20th, 2020. From these records, we derive three epidemiologically relevant metrics describing the mobility within and between comunas. The datasets made available may be useful to understand the effect of localized quarantines in containing the COVID-19 pandemic.

Genetic algorithms have proved to be a useful improvement heuristic for tackling several combinatorial problems, including the coalition structure generation problem. In this case, the focus lies on selecting the best partition from a discrete set. A relevant issue when designing a Genetic algorithm for coalition structure generation problems is to choose a proper genetic encoding that enables an efficient computational implementation. In this paper, we present a novel hybrid encoding, and we compare its performance against several genetic encoding proposed in the literature. We show that even in difficult instances of the coalition structure generation problem, the proposed approach is a competitive alternative to obtaining good quality solutions in reasonable computing times. Furthermore, we also show that the encoding relevance increases as the number of players increases.

Arsenic contamination in water remains a critical global challenge, particularly in rural and resource-limited regions. Clays have been widely studied as cost-effective and efficient adsorbents for arsenic removal. This systematic review provides a comprehensive analysis of the application of clays in arsenic adsorption, focusing on clay types, operational units, and study methodologies. The review classifies the adsorption mechanisms, highlights key factors influencing adsorption performance—such as pH, ionic strength, and surface modifications—and examines the effectiveness of various modifications. Furthermore, the study categorizes adsorption research into kinetic, iso-thermal, thermodynamic, and efficiency studies, providing insights into the state of the art and the experimental conditions that govern arsenic removal. It also discusses the scalability and practical application of clay-based adsorption technologies, emphasizing gaps in field validation, regeneration studies, and large-scale implementation. The findings highlight the potential of natural and modified clays in arsenic remediation, while underscoring the need for further research to optimize adsorption conditions and enhance sustainability in water treatment systems.

In mathematics education, studies reveal difficulties in the teaching-learning of trigonometry in secondary and higher education, due to the fact that students are not encouraged to achieve a deep conceptual understanding of abstract concepts. Several studies demonstrate that incorporating digital technologies has a positive impact on students’ learning. However, most of the existing technologies do not consider the use of the body and multiple senses. Tangible User Interfaces (TUIs) in contrast, can host bodily interactions that have the potential of enhancing learning. Nonetheless, there is a lack of applications of TUIs for trigonometry education. This study consisted in designing and validating a tangible interface for the teaching-learning of basic concepts of trigonometry. The interface hosts a pedagogical experience that privileges exploration through physical manipulation and fosters intuitive and collaborative learning. A Pre-Test was applied to 121 students to determine previous knowledge, yielding a 29.1% performance. After two sessions using the interface, the results of a Post-Test reveal an increase of 37.1%, confirming the educational effectiveness of the interface and the pedagogical experience to facilitate learning of basic concepts of trigonometry.