The importance of affect in the teaching-learning process of mathematics is undeniable. Affective responses such as math anxiety or self-confidence can have a strong influence on student performance at all educational levels, including university. Previous works show that even in mathematically oriented careers such as engineering, there are students who experience the previously mentioned anxiety. Despite the above, in Mexico this type of analysis is rare; our work aims to study the level of anxiety and self-confidence that engineering students present when they are faced with mathematical tasks. The results show that there are future engineers with very high levels of mathematical anxiety and that this is negatively correlated with their level of self-confidence.

Structural Equation Models (SEM) are very useful and, with a wide range of practical applications in many fields of science, in medicine and health sciences, have increased interest in their usefulness. This chapter is divided into three sections. The first includes concepts, notation, and theoretical aspects of SEM, such as path diagrams, measurement model, confirmatory factor analysis, structural regression, and identification model. In addition, it includes some simple examples applied to health sciences. The second section deals with the estimation and evaluation of the model. On the first topic, the methods of Maximum Likelihood (ML), Generalized Least Squares, Unweighted Least Squares, and ML with robust standard errors are addressed, as well as alternative methods to the problem of violations of the multivariate normality assumption. On the second topic, some goodness of fit statistics of the estimated model are defined, such as the chi-square statistic, Root Mean Square Error of Approximation, Tucker-Lewis Index, Comparative Fit Index, Standardized Root Mean Square Residual, and Goodness of Fit Index. The last section deals with SEM example and its implementation using the lavaan library of R software.

Anthropic activities such as agriculture, livestock, and wastewater discharges affect water quality in the Tlapaneco River in the mountain region of the state of Guerrero, México, which is a tributary of the Balsas. The river flows from the mountain region and discharges into the Pacific Ocean; the water resource in the localities mentioned is used for agriculture, recreation, and domestic activities. The aim of this study was to evaluate water quality in the stretch of influence of two localities, Patlicha and Copanatoyac. The instrument used was the Biological Monitoring Working Party biotic index (BMWP) and physicochemical parameters. Nine sampling sites were selected according to the perception of the local community with respect to disturbance; the study area was divided into three parts: high, medium, and low. Twenty-seven collections of macroinvertebrates and water were analyzed, in dry and rainy seasons, through the presence–absence of these organisms and physicochemical analysis, to evaluate water quality. The results showed that the conditions of the riverbed associated with daily activities and domestic discharges are important factors in the composition of the families. Water quality was very poor to regular, according to the macroinvertebrate assemblages collected. The BMWP index was of acceptable quality when the orders (Family) Ephemeroptera (Leptohyphidae; Leptophlebiidae; Baetidae; Ephemerellidae), Diptera (Chironomidae; Simulidae), Trichoptera (Hydropsychidae), Hemiptera (Veliidae; Corixidae), Coleoptera (Hydrophylidae), and Odonata (Lestidae) were present; in sites with poor quality, the families Chironomidae, Leptophlebiidae, Veliidae, Corixidae, Hydropsychidae, Leptohyphidae, Hydrophilidae, Baetidae, and Simuliidae were found, while in very poor quality water, only family Corixidae was present.

We introduced a novel spatial model based on the distribution of generalized extreme values (GEV) to analyze the maximum intensity levels of earthquakes with incomplete data (randomly censored) on the Pacific coast of southern Mexico using a random censorship approach. Spatiotemporal trends were modeled through a non-stationary GEV model. We used a multivariate smoothing function as a linear predictor of GEV parameters to approximate nonlinear trends. The model was fitted using a flexible semi-parametric Bayesian approach and the parameters are estimated via Markov chain Monte-Carlo (MCMC). Through a rigorous simulation study, we showed the robustness of both the model and the estimation method used. Maps of the location parameter on the spatial plane for different periods of time show the existence of local variations in the extreme values of seismicity in the study area. The results indicate strong evidence of an increase in the magnitude of earthquakes over time. A spatial map of risk with maximum intensity of earthquakes in a period of 25 years was elaborated.

Sugarcane (Saccharum spp.) is a crop of significant industrial and nutritional value, essential for producing various products. Due to its importance, genetic improvement programs involve a rigorous selection process. In this study, growth curve models were used to analyze the maturity curves of 33 hybrids (currently in the adaptability testing phase) and 6 control varieties (MEX 69-290, ITV 92-1424, CP 72-2086, COLMEX 94-8, COLMEX 95-27, RB 85-5113) during both plant and ratoon periods at the Melchor Ocampo Sugar Mill fields in Jalisco, México. With the use of clustering techniques, the materials were classified into four maturity groups: early, early–intermediate, intermediate–late, and late. Hybrids with a larger intercept and smaller slope were classified as having early and early–intermediate maturity. Conversely, hybrids with a smaller intercept and larger slope were classified as having intermediate–late and late maturity. According to the Connectivity and Dunn indexes, the DBSCAN algorithm provides the best clustering structure for materials in the plant cycle, while for the ratoon cycle, the k-means algorithm offers the best clustering structure. This highlights the versatility of each algorithm in the context of hybrid and varietal maturity analysis. These results are crucial for optimizing the productivity and sustainability of the crop, with significant implications for the sugar industry.