We study the phase space of the quintom cosmologies for a class of exponential potentials. We combine normal forms expansions and the center manifold theory in order to describe the dynamics near...

We investigate the cosmological dynamics of an up to cubic curvature correction to general relativity (GR) known as cosmological Einsteinian cubic gravity, whose vacuum spectrum consists of the graviton exclusively. Its cosmology is well posed as an initial value problem. We are able to uncover the global asymptotic structure of the phase space of this theory. It is revealed that an inflationary, matter-dominated big bang is the global past attractor, which means that inflation is the starting point of any physically meaningful cosmic history. Given that higher-order curvature corrections to GR are assumed to influence the cosmological dynamics at early times—the high energy/large curvature limit—late-time inflation is possible only if one considers a nonvanishing cosmological constant term.

In order to guarantee the sustainability of the potable water supply service, a water utility must generate improvements in its performance in an integrated manner. The objective of this research is to analyze and provide information about the components and indicators used by the water utility of Leon, Guanajuato, Mexico, which directly impact water management. The Analytic Hierarchy Process (AHP) and Fuzzy Logic (FL) methodologies were applied. The study determined the trends and evolution over time from 2002 to 2017. From the combination of both methodologies, a Water Supply Management Index was obtained with an average value of 0.79, which shows positive progress for water resource management by the water utility. However, the traditional indicators are insufficient and require particular attention. The analysis helped to identify those indicators that do impact water management and their ability to measure the sustainability of the city’s water utility. This may make it possible to monitor the progress toward the accomplishment of Sustainable Development Goal 6 (SDG 6), by performing an evaluation and thorough analysis of the status of water resources.

Five municipalities in El Bajío present the highest industrial investments: Celaya, Irapuato, León, Salamanca, and Silao. Public and private investments, further to the support received from the government, have been decisive to industrialize the zone. The official discourse to encourage these activities has emphasized the economic and social benefits for inhabitants, the decrease in the use of water volumes, and the consequent improvement of water sources in each region. The main objective of the present work is to present a global industrial impact index to evaluate the industrial impact on water management by analyzing the evolution of some parameters regarding the official data available, in order to determine whether the industry has a positive outcome on the environmental, social, economic and hydrological aspects. For this study, we use Fuzzy Logic (FL) to complete a previous study, which was conducted using the Analytic Hierarchy Process (AHP). A combination of both approaches is used to define the global impact of industrialization, and the results obtained show that the benefits claimed by governmental policies are not being achieved. The use of this proposed index may guide the decision-making processes to encourage water sustainability.

This study examines the spatio-temporal evolution of precipitation in the State of Guanajuato, Mexico, from 1981 to 2016 by analyzing monthly series from 65 meteorological stations. A rigorous data quality protocol was implemented, selecting stations with more than 30 years of continuous data and less than 10% missing values. Multiple Imputation by Chained Equations (MICE) with Predictive Mean Matching was applied to handle missing data, preserving the statistical properties of the time series as validated by Kolmogorov–Smirnov tests ($p=1.000$ for all stations). Homogeneity was assessed using Pettitt, SNHT, Buishand, and von Neumann tests, classifying 60 stations (93.8%) as useful, 3 (4.7%) as doubtful, and 2 (3.1%) as suspicious for monthly analysis. Breakpoints were predominantly clustered around periods of instrumental changes (2000–2003 and 2011–2014), underscoring the necessity of homogenization prior to trend analysis. The Trend-Free Pre-Whitening Mann–Kendall (TFPW-MK) test was applied to account for significant first-order autocorrelation (${\rho }_1 > 0.3$) present in all series. The analysis revealed no statistically significant monotonic trends in monthly precipitation at any of the 65 stations ($\alpha =0.05$). While 75.4% of the stations showed slight non-significant increasing tendencies (Kendall’s $\tau$ range: 0.0016 to 0.0520) and 24.6% showed non-significant decreasing tendencies ($\tau$ range: −0.0377 to −0.0008), Sen’s slope estimates were negligible (range: −0.0029 to 0.0111 mm/year) and statistically indistinguishable from zero. No discernible spatial patterns or correlation between trend magnitude and altitude ($\rho =-0.022$, $p>0.05$) were found, indicating region-wide precipitation stability during the study period. The integration of advanced imputation, multi-test homogenization, and robust trend detection provides a comprehensive framework for hydroclimatic analysis in semi-arid regions. These findings suggest that Guanajuato’s severe water crisis cannot be attributed to declining precipitation but rather to anthropogenic factors, primarily unsustainable groundwater extraction for agriculture.