The controlling hydrogeochemical processes of an intermontane aquifer in central Mexico were identified through multivariate statistical analysis. Hierarchical cluster (HCA) and k-means clustering analyses were applied to Na⁺, K⁺, Ca²⁺, Mg²⁺, F⁻, Cl⁻, SO₄²⁻, NO₃⁻, HCO₃⁻, As, pH and electrical conductivity in 40 groundwater samples collected from shallow and deep wells, where As and F⁻ are contaminants of concern. The effectiveness of each hierarchical and k-means clustering method in explaining solute concentrations within the aquifer and the co-occurrence of arsenic and fluoride was tested by comparing two datasets containing samples from 40 and 36 wells, the former including ionic balance outliers (>10%). When tested without outliers, cluster quality improved by about 5.4% for k-means and 7.3% for HCA, suggesting that HCA is more sensitive to ionic balance outliers. Both algorithms yielded similar clustering solutions in the outlier-free dataset, aligning with the k-means solution for all 40 samples, indicating that k-means was the more robust of the two methods. k-means clustering resolved fluoride and arsenic concentrations into four clusters (K1 to K4) based on variations in Na⁺, Ca²⁺, As, and F⁻. Cluster K2 was a Na-HCO₃ water type with high concentrations of As and F. Clusters K1, K3, and K4 exhibited a Ca-HCO₃, Na-Ca-HCO₃, and Ca-Na-HCO₃ water types, respectively, with decreasing As and F concentrations following the order K2 > K3 > K1 > K4. The weathering of evaporites and silicates and Na-Ca ion exchange with clays were the main processes controlling groundwater geochemistry. The dissolution of felsic rocks present in the aquifer fill is a likely source of As and F⁻, with evaporation acting as an important concentration factor.

Objectives: To identify early suicide risk signs on depressive subjects, so that specialized care can be provided. Various studies have focused on studying expressions on social networks, where users pour their emotions, to determine if they show signs of depression or not. However, they have neglected the quantification of the risk of committing suicide. Therefore, this article proposes a new index for identifying suicide risk in Mexico. Methodology: The proposal index is constructed through opinion mining using Twitter and the Analytic Hierarchy Process. Contribution: Using R statistical package, a study is presented considering real data, making a classification of people according to the obtained index and using information from psychologists. The proposed methodology represents an innovative prevention alternative for suicide.

The Asociación Nacional de Universidades e Instituciones de Educación Superior (ANUIES) has designed programs for academic tutoring. The Universidad Juárez del Estado de Durango (UJED) has the Programa Institucional de Tutoría (PIT) whose purpose is to minimizeschool dropout and progress delays. FewPIT evaluations have had the participation of all the educational actors involved in this program. This study’sgoal was to analyze the statistical relationships among the evaluations of the educational actors involved at the PIT in UJED. This exploratory and descriptive work was carried out through the application and statistical analysis of a virtual questionnaire designed by the Red Regional Noreste de Tutoría (RRNET), to which UJED belongs. There were3,859 participants,involving Mentees, Mentors, Tutoring Coordinators and Directors at the Academic Unit, and Institutional Tutoring Coordinator. The analysis foundthat the perception of academic figures does have an impact on the way students perceive this program.