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In this paper, we tackle the problem of forecasting future pandemics by training models with a COVID-19 time series. We tested this approach by producing one model and using it to forecast a non-trained time series; however, we limited this paper to the eight states with the highest population density in Mexico. We propose a generalized pandemic forecasting framework that transforms the time series into a dataset via three different transformations using random forest and backward transformations. Additionally, we tested the impact of the horizon and dataset window sizes for the training phase. A Wilcoxon test showed that the best transformation technique statistically outperformed the other two transformations with 100% certainty. The best transformation included the accumulated efforts of the other two plus a normalization that helped rescale the non-trained time series, improving the sMAPE from the value of 25.48 attained for the second-best transformation to 13.53. The figures in the experimentation section show promising results regarding the possibility of forecasting the early stages of future pandemics with trained data from the COVID-19 time series. [ABSTRACT FROM AUTHOR]

Future climate change is expected to increase the risk and severity of wildland fires in tropical regions. Synoptic-scale fire weather conditions in Mexico were carefully analyzed using 20 years of satellite hotspot and rainfall data, hourly weather data, and various climate data. Fire analysis results showed that eighty-four percent of all fires in Mexico occurred south of 22° N. Southwest Mexico (SWM, N < 22°, 94–106° W) and Southeast Mexico (SEM, N < 22°, 86–94° W), account for 50% and 34% of all fires in Mexico. Synoptic-scale analysis results using hourly data showed that westerly wind sea breezes from the Pacific Ocean blow toward the coastal land areas of the SWM while easterly wind sea breezes from the Caribbean blow into the SEM. The most sensitive weather parameters were "relative humidity" for the SWM and "temperature" for the SEM. The fire-related indices selected were "precipitable water vapor anomaly" for the SWM and "temperature anomaly" for the SEM. The SWM fire index suggests that future fires will depend on dryness, while the SEM fire index suggests that future fires will depend on temperature trends. I do hope that this paper will improve local fire forecasts and help analyze future fire trends under global warming in Mexico. [ABSTRACT FROM AUTHOR]

In this paper, four probability functions are compared with the purpose of establishing a methodology to improve the accuracy of wind energy estimations in a desert city in Northwestern Mexico. Three time series of wind speed data corresponding to 2017, 2018, and 2019 were used for statistical modeling. These series were recorded with a sonic anemometer at a sampling frequency of 10 Hz. Analyses based on these data were performed at different stationarity periods (5, 30, 60, and 600 s). The estimation of the parameters characterizing the probability density functions (PDFs) was carried out using different methods; the statistical models were evaluated by the coefficient of determination and Nash–Sutcliffe efficiency coefficient, and their accuracy was estimated by the measured quadratic error, mean square error, mean absolute error, and mean absolute percentage error. Weibull, using the energy pattern factor method, and Gamma, using the Method of Moments, were the probability density functions that best described the statistical behavior of wind speed and were better at estimating the generated energy. We conclude that the proposed methodology will increase the confidence of both wind speed estimation and the energy supplied by small-scale wind installations. [ABSTRACT FROM AUTHOR]

Anticipating and planning for the urgent response to large-scale disasters is critical to increase the probability of survival at these events. These incidents present various challenges that complicate the response, such as unfavorable weather conditions, difficulties in accessing affected areas, and the geographical spread of the victims. Furthermore, local socioeconomic factors, such as inadequate prevention education, limited disaster resources, and insufficient coordination between public and private emergency services, can complicate these situations. In large-scale emergencies, multiple demand points (DPs) are generally observed, which requires efforts to coordinate the strategic allocation of human and material resources in different geographical areas. Therefore, the precise management of these resources based on the specific needs of each area becomes fundamental. To address these complexities, this paper proposes a methodology that models these scenarios as a multi-objective optimization problem, focusing on the location-allocation problem of resources in Mass Casualty Incidents (MCIs). The proposed case study is Mexico City in a earthquake post-disaster scenario, using voluntary geographic information, open government data, and historical data from the 19 September 2017 earthquake. It is assumed that the resources that require optimal location and allocation are ambulances, which focus on medical issues that affect the survival of victims. The designed solution involves the use of a metaheuristic optimization technique, along with a parameter tuning technique, to find configurations that perform at different instances of the problem, i.e., different hypothetical scenarios that can be used as a reference for future possible situations. Finally, the objective is to present the different solutions graphically, accompanied by relevant information to facilitate the decision-making process of the authorities responsible for the practical implementation of these solutions. [ABSTRACT FROM AUTHOR]

On 26 April 2017, Mexico formally adopted the 2030 Sustainable Development Agenda to link the national government to local governments, the private sector, civil society and academia. The restoration of heritage residential buildings (recovery programme) and the construction of new residential buildings aim to create a diversified environment for populations at different economic levels. However, the restoration programme faces conservation challenges. Given this context, this paper presents the results of in-depth, semi-structured interviews conducted with stakeholders in Mexico's heritage and energy sectors. The duration of each interview was approximately two hours, with 52,372 total interview words. The paper identifies prevailing opinions regarding prioritising historical values, energy efficiency, historic buildings and users concerning Mexico City's Historical Centre, a World Heritage Site needing a more appropriate sustainable development plan. Using grounded theory and thematic analysis, the interview data were analysed based on the interrelationship between thermal comfort, energy efficiency and heritage conservation changes over time. The results of this research will strengthen our understanding of the interventions and processes involved in managing and living in this World Heritage Site and its future impacts on buildings. The approach also underscores the importance of how stakeholders prioritise different values in making energy efficiency-promoting decisions and enhances awareness of the decision-making process and actions adopted by heritage building users. Thus, understanding the dynamic interrelationship between values, users and energy could improve the sustainable management of heritage sites and future development. [ABSTRACT FROM AUTHOR]

This paper tackles the challenge of time series forecasting in the presence of missing data. Traditional methods often struggle with such data, which leads to inaccurate predictions. We propose a novel framework that combines the strengths of Generative Adversarial Networks (GANs) and Bayesian inference. The framework utilizes a Conditional GAN (C-GAN) to realistically impute missing values in the time series data. Subsequently, Bayesian inference is employed to quantify the uncertainty associated with the forecasts due to the missing data. This combined approach improves the robustness and reliability of forecasting compared to traditional methods. The effectiveness of our proposed method is evaluated on a real-world dataset of air pollution data from Mexico City. The results demonstrate the framework's capability to handle missing data and achieve improved forecasting accuracy. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the morphology and columnar microphysical properties of atmospheric aerosols in Mexico City (MC) for the period 2022–2023. The morphological study focused on the structure description of soot particles and tar balls (TB). By transmission electron microscope (TEM) and scanning electrode microscope (SEM), voluminous soot aggregates mixed with TBs were observed. The chemistry shows that both soot and TBs are mostly carbonaceous species with well-defined morphologies. On the other hand, the columnar aerosol microphysical properties recovered from AERONET show that the particles have a bimodal aerosol size distribution (ASD) with two modes: fine and coarse. The ASD remains constant without showing significant seasonal changes, only with some variability for coarse particles. The aerosol optical depth (AOD) value is significantly high, typical of urban areas. The real (n) and imaginary (k) parts of the complex refractive index (CRI) were obtained from the photometric measurements. The CRI values show seasonal variations, with spring being the season with the highest values for n, while the highest values for k were measured in winter. [ABSTRACT FROM AUTHOR]

To understand urbanization across the Global South, it is indispensable to consider situated heterogeneous urban situations shaped by global and local forces and their intersections. In the case of Mexico, the political and economic desire for globalization has extended beyond the great metropolis of Mexico City to mid-size cities triggering the formulation of their own urban strategies to become global. This paper explores the connections between neoliberal public policy, globalization, urban modeling, and socio-territorial sustainability in the territorial binomial of the city of Puebla and the municipality of San Andrés Cholula in the period of 2011–2017 and its current consequences, addressed by the local planning route map, and informed by the Orange Economy-guide of the Inter-American Development Bank (IDB), using relevant bibliographical sources, mapping, interviews of stakeholders, and fieldwork. The ultimate purpose of the research project described herein is to provide a multi-dimensional analysis of the development of the territorial situation of the Puebla-San Andrés Cholula-urban binomial, and of its current and potential future consequences, offering supporting information for its urban planning. The research results exposed here reveal urban modeling processes informed by the Global North urban globalization theory, development of global cities in the Global South, local socio-territorial dynamics characterized by economic and political interests imprinted in the public policy, and socio-territorial patterns inherited from the colonial past, resulting in socio-economic and racial discrimination, population displacements, real estate speculation, and risking ecological and environmental sustainability. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present a performance-based method to estimate uniform risk spectra (URS) for the seismic design and assessment of structures. These spectra, computed with the proposed methodology, provide the lateral capacity (in terms of spectral acceleration) that should be given to a structure, characterized by a reference single degree of freedom system, to achieve a predetermined exceedance rate of economic loss. This procedure involves the seismic hazard assessment necessary to define a seismic design level consistent with the accepted loss value, using a large enough number of synthetic seismic records of several magnitudes, which were obtained by means of an improved empirical Green function method. The statistics of the expected losses of a reference single degree of freedom system are obtained using Monte Carlo simulation, considering the seismic demand and the lateral strength of the structure as random variables. The method is divided into two main stages: (1) definition of the seismic hazard at the site of interest and (2) the probabilistic analysis of the seismic performance in terms of an economical loss ratio of nonlinear SDOF. To illustrate the proposed methodology and, subsequently, to validate it, a URS was computed for a site located in the Mexico City lake-bed zone, and its use in the design of three reinforced concrete frames is shown. The results show that the proposed spectra provide a sufficient approximation between the seismic risk level considered in the seismic design and that of the designed structure. It is concluded that the proposed procedure is a significant improvement over others considered in the literature and a useful research tool for the further development of risk-based earthquake engineering. [ABSTRACT FROM AUTHOR]

Early identification of anomalies (such as leakages or sensor failures) in urban water distribution systems is critical to mitigating water scarcity in cities and is a challenge in water resource management. Several data-driven methods based on machine learning algorithms have been proposed in the literature for leakage detection in urban water distribution systems. Still, most of them are challenging to implement due to their complexity and requirements of vast amounts of reliable data for proper model generation. In addition, the required infrastructure and instrumentation to collect the data needed to train the models could be unaffordable. This paper presents the use and comparison of Autoregressive Integrated Moving Average models and Transfer Function models generated via the Box–Jenkins approach to modeling the water flow in water distribution systems for anomaly detection. The models were fit using water flow data from tanks operating in a branch of the water distribution system of Mexico City. The results showed that both methods helped select the best model type for each variable in the analyzed water branch, with Seasonal ARIMA models achieving a lower mean absolute percentage error than the fitted Transfer Function models. Furthermore, this methodology can be adjusted to different time windows to generate alerts at different rates and does not require a large sample size. The generated anomaly detection models could improve the efficiency of the water distribution system by detecting anomalies such as wrong measurements and water leakages. [ABSTRACT FROM AUTHOR]

Featured Application: To date, the 'values' associated with 'heritage buildings' have received little attention in designing technical interventions for energy efficiency. This may be due to a fear that modern interventions for improving energy performance clash with heritage conservation, especially conservation of original features. We argue that energy efficiency interventions and heritage conservation can co-exist if an in-depth understanding of people's heritage values and attitudes is obtained. This paper adds to our limited knowledge of residents' approaches to heritage conservation and energy efficiency. It does so by presenting the first study of its kind in Mexico's City Historic Centre (a World Heritage Site since 1987). The results reveal the type of heritage values that residents assigned to their buildings when seeking to achieve thermal comfort and energy efficiency in heritage buildings. With building construction representing one of the largest sectors responsible for the use of natural resources, retrofitting existing heritage buildings becomes a necessity, albeit a challenging one. The emergence of specific guidance on retrofitting heritage buildings has unveiled more than never the need to understand how residents negotiate, thermal comfort, energy efficiency, and heritage conservation decisions. The paper reports the complexity of the decision-making process of residents of heritage buildings in the Historic Centre of Mexico City regarding energy efficiency, intending to improve thermal comfort and reduce energy consumption while preserving heritage values. The study involved in-depth semi-structured interviews with users of heritage buildings that were thematically analysed, complemented by the monitoring of internal environmental conditions and system dynamics analysis. The results show that although the residents perceived the buildings' temperature as poor, passive thermal comfort actions (e.g., wearing more clothes and closing windows) were preferred against invasive retrofitting solutions for thermal comfort due to residents' resistance to a potential loss in the buildings' values and the high cost of changes. The degree of change necessary for maintenance, renovation, and actions for improving the thermal comfort of a heritage building is related to values and to their preservation for future generations. The users' changes were limited to small-scale interventions in floors and ceilings while avoiding touching what they consider essential to preserve and protect (i.e., social and cultural values). Integrating the user into the decision-making process would enhance the long-term continuity and sustainability of retrofitting policies and guidelines, thus avoiding losing heritage-built stock. [ABSTRACT FROM AUTHOR]

Ecological Niche Models (ENM) are tools used to predict suitability, based on climatic variables selected and occurrence data of the target species, and characterize the environmental space. Sawflies (Hymenoptera: Diprionidae) are one of the main factors threatening forest health in Mexico, with cyclical population outbreaks and a wide range of hosts. In the present paper, we calculate the climatic niche in Mexico of three diprionids, Neodiprion abietis (Harris), N. omosus Smith, and Zadiprion rohweri (Middleton); the first and the latter with recent records in Mexico, and N. omosus with presence in Mexico and Guatemala; contrasting them against the distribution records of host species in the country. The climatic suitability of N. abietis was high in the Sierra Madre Occidental where its hosts, Pinus ponderosa, P. strobiformis, and P. menziesii are distributed. For N. omosus, the environmental suitability was projected towards the Southern Altiplano, where it coincides with a small presence of its hosts P. leiophylla and P. ayacahuite; however, it was possible to calculate its coincidence with more hosts in other biogeographic provinces. Pinaceae species considered under threat, Abies concolor, P. monophylla, and P. strobiformis, have populations within the environmental suitability of the sawflies. [ABSTRACT FROM AUTHOR]

Bursera fagaroides, popularly used in México, possesses bioactive lignans. These compounds are low in the bark, and its extraction endangers the life of the trees. The aim of the present investigation was to search for alternative sources of cytotoxic compounds in B. fagaroides prepared as leaves and in vitro callus cultures. The friable callus of B. fagaroides was established using a combination of plant growth regulators: 4 mgL−1 of 2,4-dichlorophenoxyacetic acid (2,4-D), 1 mgL−1 Naphthaleneacetic Acid (NAA) and 1 mgL−1 Zeatin. The maximum cell growth was at day 28 with a specific growth rate of μ = 0.059 days−1 and duplication time td = 11.8 days. HPLC quantification of the dichloromethane callus biomass extract showed that Scopoletin, with a concentration of 10.7 µg g−1 dry weight, was the main compound inducible as a phytoalexin by the addition of high concentrations of 2,4-D, as well as by the absence of nutrients in the culture medium. In this same extract, the compounds γ-sitosterol and stigmasterol were also identified by GC-MS analysis. Open column chromatography was used to separate and identify yatein, acetyl podophyllotoxin and 7′,8′-dehydropodophyllotoxin in the leaves of the wild plant. Cytotoxic activity on four cancer cell lines was tested, with PC-3 prostate carcinoma (IC50 of 12.6 ± 4.6 µgmL−1) being the most sensitive to the wild-type plant extract and HeLa cervical carcinoma (IC50 of 72 ± 5 µgmL−1) being the most sensitive to the callus culture extract. [ABSTRACT FROM AUTHOR]

Background: Refractive errors, including myopia, hyperopia, and astigmatism, are the leading causes of visual impairment in school-aged children and can significantly impact their academic performance and quality of life. This study aimed to assess the prevalence of refractive errors among school children from economically disadvantaged areas in Northwest México, using a consistent methodology to facilitate comparison with global data. Methods: We adopted the Refractive Error Study in Children (RESC) protocol by the World Health Organization to examine the prevalence of myopia, hyperopia, and astigmatism. The study comprised a systematic sampling of children aged 6 to 18 years from diverse schools in Northwest México. Trained optometrists conducted visual acuity testing and autorefraction, while ophthalmologists performed cycloplegic refraction to ensure accuracy. Results: The study found a myopia (SE ≤−1.50 D at least one eye) prevalence of 14.55% (95% CI: 13.27–15.91), with a higher incidence in females (6.92%) compared to males (6.00%) in at least one eye. Hyperopia (SE ≥ +1.00 D at least one eye) was less common, at 3.23% (95% CI: 2.61–3.95), with a slightly higher occurrence in males in at least one eye. Astigmatism (Cylinder ≥ 0.75 D at least one eye) was present in 18.63% (95% CI: 17.21–20.12) of the students in at least one eye, with no significant difference between genders. These findings are consistent with other studies in regions such as Puerto Rico and Iran, indicating widespread refractive error issues among schoolchildren. Conclusions: The high prevalence of refractive errors, particularly myopia and astigmatism, highlights the critical need for regular vision screenings in schools and the implementation of public health interventions to provide corrective eyewear. Our study confirms the importance of utilizing standardized methodologies like the RESC protocol to compare refractive error prevalence across different geographical and socio-economic contexts, thereby informing global public health strategies. [ABSTRACT FROM AUTHOR]

Globally, there is growing concern over the presence of lead (Pb) in foods because it is a heavy metal with several toxic effects on human health. However, monitoring studies have not been conducted in Mexico. In this study, we estimated the concentrations of Pb in the most consumed foods and identified those that exceeded the maximum limits (MLs) for Pb in foods established by the International Standards. Based on the Mexican National Health and Nutrition Survey, 103 foods and beverages were selected and purchased in Mexico City retail stores and markets. Samples were analyzed twice using atomic absorption spectrophotometry. Values above the limit of quantification (0.0025 mg/kg) were considered to be detected. The percentage of detected values was 18%. The highest concentration was found in infant rice cereal (1.005 mg/kg), whole wheat bread (0.447 mg/kg), pre-cooked rice (0.276 mg/kg), black pepper (0.239 mg/kg), and turmeric (0.176 mg/kg). Among the foods with detected Pb, the levels in infant rice cereal, whole wheat bread, pre-cooked rice, and soy infant formula exceeded the MLs. The food groups with the highest percentages of exceeded MLs were baby foods (18%) and cereals (11%). Monitoring the concentration of contaminants in foods is essential for implementing food safety policies and protecting consumer health. [ABSTRACT FROM AUTHOR]

Leptospirosis is a neglected zoonotic disease that commonly affects cattle, pigs, horses, and dogs in many countries. Infection in dogs is usually subclinical, but acute cases of leptospirosis may occur along with systemic failure, which may become fatal. After recovery from an acute infection, dogs may become asymptomatic carriers and shed pathogenic leptospires through urine for long periods of time. Here, a study of ten different cases of leptospirosis is presented, showing the relevance of dogs as asymptomatic carriers of pathogenic Leptospira. The diagnosis was confirmed via isolation and further serological and genetic identification. Four Leptospira isolates (LOCaS28, 31, 34, and 46) were obtained from the kidneys and urine samples of 58 dogs destined for destruction (6.89%) at a Canine Control Center in Mexico City. No spirochetes were observed in the urine samples of those Leptospira-positive dogs examined under dark-field microscopy, and no clinical signs of disease were observed either. Six additional isolates were obtained: two came from asymptomatic carrier dogs (CEL60 and UADY22); another isolate came from an asymptomatic dog that was a pack companion of a clinically ill dog with fatal leptospirosis (AGFA24); and finally, three isolates were taken from dogs that died of leptospirosis (LOCaS59, Citlalli, and Nayar1). Nine out of the ten isolates were identified as being from the serogroup Canicola via cross-absorption MAT using reference strains and specific antisera, and their identity was genetically confirmed as Canicola ST34 via multi-locus sequencing typing (MLST). In contrast, the isolate Nayar1 was identified as serovar Copenhageni ST2. Interestingly, the asymptomatic dogs from which Leptospira isolates were recovered consistently showed high antibody titers in the microscopic agglutination test (MAT), revealing values of at least 1:3200 against serogroup Canicola and lower titer values against other serogroups. Isolates showed different virulence levels in the hamster model. Taken as a whole, all these findings confirmed that dogs may act as asymptomatic carriers of pathogenic leptospires and possibly spread them out to the environment, thus representing an active public health risk. The results also showed that the Canicola ST34 clone is the most prevalent Leptospira serovar in dogs in Mexico, and finally that the old-fashioned MAT is a good alternative for the detection of presumptive Leptospira asymptomatic carrier dogs. [ABSTRACT FROM AUTHOR]

In México, the utilization of fast-growing plant species for biomass production presents transportation-related issues such as freshness reduction, the transportation of large volumes with minimal weight due to low density, limited storage availability, and logistical challenges. To enhance understanding in this field, the research aimed to evaluate the densification potential of a variety of organic materials, with a specific emphasis on the biomass derived from eight species of rapidly growing plants, three animal species' manure, and concentrated feed. After conditioning, 100 g samples underwent particle size analysis and were categorized into seven sizes. Pellets and briquettes (40 g, 10% moisture, 15 MPa pressure, 5 min processing, 80 °C temperature) were produced and evaluated for bulk density (BD) and pellet (PD) and briquette durability (BDU). The predominant particle sizes were 0.850 mm and 0.425 mm. Original biomass bulk density (OBBD) varied notably, with ovine manure (0.50 g cm−3) and cattle feed (0.49 g cm−3) exhibiting the highest values. Caprine manure (0.83 g cm−3) and ovine manure (0.78 g cm−3) yielded the densest pellets at 1.76 and 1.84 g cm−3, respectively. Apple tree pellets achieved premium quality with the highest hardness (97.9%). Cattle manure (1.25 g cm−3) and cattle feed (1.25 g cm−3) had the densest briquettes, with notable BBD/OBBD ratios in pine sawdust (4.6) and corn (4.5). Caprine manure and Acacia biomass briquettes showed premium quality with the highest hardness (99.1%), emphasizing densification variations and the need for tailored approaches based on organic material characteristics. [ABSTRACT FROM AUTHOR]

The presence of deep convective clouds is directly related to potential convective hazards, such as lightning strikes, hail, severe storms, flash floods, and tornadoes. On the other hand, Mexico has a limited and heterogeneous network of instruments that allow for efficient and reliable monitoring and forecasting of such events. In this study, a quasi-real-time framework for deep convective cloud identification and modeling based on machine learning (ML) models was developed. Eight different ML models and model assembly approaches were fed with Interest Fields estimated from Advanced Baseline Imager (ABI) sensor data on the Geostationary Operational Environmental Satellite-R Series (GOES-R) for one region in central Mexico and another in northeastern Mexico, both selected for their intense convective activity and high levels of vulnerability to severe weather. The results indicate that a simple approach such as Logistic Regression (LR) or Random Forest (RF) can be a good alternative for the identification and simulation of deep convective clouds in both study areas, with a probability of detection of (POD) ≈ 0.84 for Los Mochis and POD of ≈ 0.72 for Mexico City. Similarly, the false alarm ratio (FAR) ≈ 0.2 and FAR ≈ 0.4 values were obtained for Los Mochis and Mexico City, respectively. Finally, a post-processing filter based on lightning incidence (Lightning Filter) was applied with data from the Geostationary Lightning Mapper (GLM) of the GOES-16 satellite, showed great potential to improve the probability of detection (POD) of the ML models. This work sets a precedent for the implementation of an early-warning system for hazards associated with intense convective activity in Mexico. [ABSTRACT FROM AUTHOR]

The aim of this paper is to design an approach to evaluate the expected efficiency and performance of future airport infrastructure. First, an airport sampling method to select similar airports is developed based on socioeconomic and operational airport variables that are summarized in a proxy variable; second, the ARIMA-GARCH-Bootstrap method is applied to forecast the selected outputs (PAX and ATMS) whilst the selected inputs (Cities, Gates, Runaways, Airport Size, Pax carriers, and Num. of employees) remain constant; and third, the VRS-OO and the CRS-OO DEA models are implemented to evaluate the efficiency and performance of the airports in the current and future years. The proposed approach is used to evaluate the future airport infrastructure of the new Mexico City Airport against 19 representative worldwide airport hubs. The proposed approach is applied to analyze the Mexico City Airport multi-airport system infrastructure as a case study. The results show that this multi-airport system requires more airside infrastructure that must be added by the new Mexico City Airport, airlines should operate aircrafts with more capacity to serve more PAX per ATM, and airlines must open new connections at the new Mexico City Airport to increase the expected efficiency and performance of this multi-airport system. [ABSTRACT FROM AUTHOR]

This study investigates the relationships between lexical development and inhibition, as well as morphosyntax and inhibition, in typically developing monolingual Spanish-speaking children. Recent studies of the relationship between lexical development and inhibition suggest that, as the size of the lexicon increases, so does inhibitory ability. However, the relationship between grammar and inhibition seems more controversial. The work distinguishing the relationships between inhibition and lexicon vs. grammar have been carried out in English, which has relatively impoverished inflectional morphology. Because the relationships considered in the literature are hypothetically not language-particular to English, but rather claims about cognition in general, we would expect to find that they also hold in other languages, including languages with richer morphology, such as Spanish. These considerations led us to ask the following: are expressive and receptive measures of the lexicon and morphosyntax predictive of typically developing monolingual child Spanish-speakers' inhibitory ability? A sample of 82 monolingual, typically developing Spanish-speaking children in Mexico City were tested with 5 lexical measures, 4 morphosyntax measures, and the Flanker Task measure of inhibition. Results showed that all lexical and morphosyntactic variables correlated significantly with Flanker (p < 0.01), except for Number of Different Words (NDW), calculated on the spontaneous production sample. Therefore, inhibition is predicted by lexical development in child Spanish. Additionally, an ever-increasing set of competitor morphological forms requires an ever-increasing inhibitory ability as well. [ABSTRACT FROM AUTHOR]

The mistletoe Phoradendron velutinum (P. velutinum) is a pest that spreads rapidly and uncontrollably in Mexican forests, becoming a serious problem since it is a cause of the decline of 23.3 million hectares of conifers and broadleaves in the country. The lack of adequate phytosanitary control has negative social, economic, and environmental impacts. However, pest management is a challenging task due to the difficulty of early detection for proper control of mistletoe infestations. Automating the detection of this pest is important due to its rapid spread and the high costs of field identification tasks. This paper presents a Genetic Programming (GP) approach for the automatic design of an algorithm to detect mistletoe using multispectral aerial images. Our study area is located in a conservation area of Mexico City, in the San Bartolo Ameyalco community. Images of 148 hectares were acquired by means of an Unmanned Aerial Vehicle (UAV) carrying a sensor sensitive to the R, G, B, red edge, and near-infrared bands, and with an average spatial resolution of less than 10 cm per pixel. As a result, it was possible to obtain an algorithm capable of classifying mistletoe P. velutinum at its flowering stage for the specific case of the study area in conservation area with an Overall Accuracy (OA) of 96% and a value of fitness function based on weighted Cohen's Kappa ( k w ) equal to 0.45 in the test data set. Additionally, our method's performance was compared with two traditional image classification methods; in the first, a classical spectral index, named Intensive Pigment Index of Structure 2 (SIPI2), was considered for the detection of P. velutinum. The second method considers the well-known Support Vector Machine classification algorithm (SVM). We also compare the accuracy of the best GP individual with two additional indices obtained during the solution analysis. According to our experimental results, our GP-based algorithm outperforms the results obtained by the aforementioned methods for the identification of P. velutinum. [ABSTRACT FROM AUTHOR]

The aim of this study is to put forward an approach designed to calculate and sum up discrepancies between the actual food acquisition or intake and any standard or norm. Based on secondary analysis of cross-sectional data from the Mexican National Survey of Household Income and Expenditure, our proposed method to produce classes of entropy-based Diet Adherence Indices generates a Food Basket Adherence Index (FBAI) for Mexico City (2129 households). Findings suggest that it is possible to measure and decompose diet adherence using a cross entropy measure. Using food expenditure data and a normative food basket for Mexico City results, we show households' deviations from the suggested norm for different food groups. The average FBAI was 0.44, far above the minimum score of 0 which would indicate full adherence to the normative food basket. Our measure has a distribution wide enough to detect meaningful changes and distinguish between groups with known differences, providing important new insights on the linkages between home food environments and income distribution, and food insecurity and household distribution. [ABSTRACT FROM AUTHOR]

Large-scale infrastructure monitoring and vulnerability assessment are crucial for the preservation and maintenance of built environments. To ensure the safety of urban infrastructure against natural and man-made disasters, constant monitoring is crucial. To do so, satellite Earth observation (EO) is being proposed, particularly radar-based imaging, because it allows large-scale constant monitoring since radar signals are not blocked by clouds and can be collected during both day and night. The proposed methodology for large-scale infrastructure monitoring and vulnerability assessment is based on MT-InSAR time series analysis. The homogeneity of the year-to-year displacement trend between each point and its surrounding points is evaluated to determine whether the area is a stable or vulnerable zone. To validate the methodology, four case studies of recently collapsed infrastructures are analyzed. The results indicate the potential of the proposed methodology for predicting and preventing structural collapses. [ABSTRACT FROM AUTHOR]

This paper tests if air pollution serves as a carrier for SARS-CoV-2 by measuring the effect of daily exposure to air pollution on its spread by panel data models that incorporates a possible commonality between municipalities. We show that the contemporary exposure to particle matter is not the main driver behind the increasing number of cases and deaths in the Mexico City Metropolitan Area. Remarkably, we also find that the cross-dependence between municipalities in the Mexican region is highly correlated to public mobility, which plays the leading role behind the rhythm of contagion. Our findings are particularly revealing given that the Mexico City Metropolitan Area did not experience a decrease in air pollution during COVID-19 induced lockdowns. [ABSTRACT FROM AUTHOR]

Sustainable building design, such as the Passivhaus standard, seeks to minimise energy consumption, while improving indoor environmental comfort. Very few studies have studied the indoor air quality (IAQ) in Passivhaus homes outside of Europe. This paper presents the indoor particulate matter (PM2.5), carbon dioxide (CO2), and total volatile organic compounds (tVOC) measurements of the first residential Passivhaus in Latin America. It compares them to a standard home in Mexico City. Low-cost monitors were installed in the bedroom, living room, and kitchen spaces of both homes, to collect data at five-minute intervals for one year. The physical measurements from each home were also compared to the occupants' IAQ perceptions. The measurements demonstrated that the Passivhaus CO2 and tVOC annual average levels were 143.8 ppm and 81.47 μg/m3 lower than the standard home. The PM2.5 in the Passivhaus was 11.13 μg/m3 lower than the standard home and 5.75 μg/m3 lower than outdoors. While the results presented here cannot be generalised, the results suggest that Passivhaus dwellings can provide better and healthier indoor air quality in Latin America. Further, large-scale studies should look at the indoor environmental conditions, energy performance, and dwelling design of Passivhaus dwellings in Latin America. [ABSTRACT FROM AUTHOR]

When conducting an analysis of nature's time series, such as meteorological ones, an important matter is a long-range dependence to quantify the global behavior of the series and connect it with other physical characteristics of the region of study. In this paper, we applied the Higuchi fractal dimension and the Hurst exponent (rescaled range) to quantify the relative trend underlying the time series of historical data from 17 of the 34 weather stations located in the Río Bravo-San Juan Basin, Mexico; these data were provided by the National Water Commission CONAGUA) in Mexico. In this way, this work aims to perform a comparative study about the level of persistency obtained by using the Higuchi fractal dimension and Hurst exponent for each station of the basin. The comparison is supported by a climate clustering of the stations, according to the Köppen classification. Results showed a better fitting between the climate of each station and its Higuchi fractal dimension obtained than when using the Hurst exponent. In fact, we found that the more the aridity of the zone the more the persistency of rainfall, according to Higuchi's values. In turn, we found more relation between the Hurst exponent and the accumulated amount of rainfall. These are relations between the climate and the long-term persistency of rainfall in the basin that could help to better understand and complete the climatological models of the study region. Trends between the fractal exponents used and the accumulated annual rainfall were also analyzed. [ABSTRACT FROM AUTHOR]

Zinc phosphide is a rodenticide that is used in agricultural, urban and industrial environments in México. After ingestion, it reacts with hydrochloric acid, hydrolyzing into phosphine. It causes cellular hypoxia via mitochondrial toxicity, resulting in multiple organ dysfunction and death. There is no antidote or specific treatment for zinc phosphide toxicity. We present the case of a 45-year-old female who ingested zinc phosphide with suicidal intent. On arrival at the emergency department, she had multisystemic disorders. Supportive care, decontamination and antidotal therapy were initiated. Subsequently, she evolved to clinical improvement with a resolution of the biochemical abnormalities of tissue hypoperfusion. She was discharged on day 7 without complications. In this review, we provide updated therapeutic options and discuss their specific pathophysiological basis. [ABSTRACT FROM AUTHOR]

Looking for regular statistical trends of relations in schools, we constructed 42 independent weighted directed networks of simultaneous friendship and animosity from surveys we made in the Mexico City Metropolitan area in classrooms with students of different ages and levels by asking them to nominate and order five friends and five foes. However, the data show that older students nominated fewer than the five required five foes. Although each classroom was independent of the others, we found several general trends involving students of different ages and grade levels. In all classrooms, friendship entropy was found to be higher than enmity entropy, indicating that fewer students received enmity links than received friendship nominations. Popular agents exhibited more reciprocal nominations among themselves than less popular agents, and opposite-sex friendships increased with age. [ABSTRACT FROM AUTHOR]

Cities consume most of the energy used worldwide and are the largest emitters of greenhouse gases (GHGs) that cause global warming, mainly from the road transport sector. In megacities, the light vehicle fleet is responsible for most of the emissions in the sector. Among this fleet, light commercial vehicles (CVs), which have grown to support instant delivery services demand, are also responsible for emissions and traffic congestion. Due to the urgency to reduce transport impacts, emission mitigation strategies are required. Aligned with this aim, this article evaluates GHG emissions along the entire process of energy production, called the operating trajectory, and also known as Well-To-Wheel (WTW), in four combinations of transportation modes for last-mile delivery services, using light CVs, such as electric or diesel vans, and electric cargo bikes (E-bikes). The analysis is firstly conducted in a local area of Mexico City and subsequently compared to other countries around the world. In this respect, the main result of this article shows that in the case study conducted in the Metropolitan Zone of the Valley of Mexico, the energy consumption of a given route for an electric van combined with E-bikes generates 24% less GHG emissions than a diesel van combined with E-bikes. Therefore, the achievement of effective mitigation strategies for GHG emissions reduction through vehicle electrification requires WTW emission analysis and quantification, optimal route design, a combination of sustainable transport modes and clean energy generation. [ABSTRACT FROM AUTHOR]

Featured Application: Understanding leachate treatment systems through organic matter monitoring. The presence of refractory compounds in stabilized leachates makes treatment complex. In leachate treatment systems, the lack of data on the characterization of leachates and effluents makes it difficult to track and explain the evolution of organic matter. In this study, the fractionation of chemical oxygen demand (COD) and humic substances, including humic acids (HA) and fulvic acids (FA), in addition to the application of spectroscopic techniques (Fourier transform infrared and ultraviolet–visible spectroscopy), were used to solve this data gap. A treatment system was proposed: electro-coagulation (EC) and electro-oxidation (EO). Optimal conditions (maximum COD removal) were EC, I: 4.3 A, stirring: 120 revolutions per minute, and pH: 7; EO, added NaCl: 1.0 g L−1, distance between electrodes: 0.75 cm, I: 2 A, and pH: 7. Under optimal conditions COD, HA, and FA % removals were achieved: EC: 64, 69, and 63; EO: 83, 40, and 55; respectively. In EC, the % of biodegradable COD increased from 26 to 39 and in EO it increased from 39 to 58. The biodegradability index increased from 0.094 to 0.26 with EC and reached 0.46 with EO. The generated data allowed us to establish the transformations of organic matter in the process, which was useful for understanding the processes and functioning as a tool for improving treatment systems. [ABSTRACT FROM AUTHOR]

This research aims to compare, from a technical and financial perspective, the application of biological (methane-capture) and thermal (incineration) treatments of waste in Mexico City in order to generate clean energy. For each alternative, pessimist (50%), realistic (80%), and optimistic (100%) scenarios were considered in terms of the efficiency collection rates of methane and the efficiency of the capacity conversion factor for incineration. For the methane project, the LandGEM model was used to evaluate the potential generation of methane. In order to calculate the electricity output that could be generated through incineration, we relied on two key factors: the total amount of heat that could be generated by burning the waste and the average level of moisture in the waste material. The evaluation resulted in an annual energy generation of 206.09 GWh for methane and 4183.39 GWh for incineration, both in the realistic scenario. Both projects reported positive financial indicators with a discount rate of 12%. Incineration resulted in a net present value of USD 706,377,303 and an internal rate of return of 23% versus USD 4,975,369 and 24% for the methane project. However, the incineration project only became feasible by omitting financing. Incineration resulted in a payback period that was lower by a ratio of 2:1 compared to methane, but the levelized cost of energy resulted in higher figures (USD 216.92). The aim of these findings is to support the decision-making process for the creation and implementation of sustainable energy strategies based on circular economy principles in Mexico and other similar regions across the globe. [ABSTRACT FROM AUTHOR]

This paper presents bioenergy value chain modelling to estimate the biomass and bioenergy cost of production and biomass netback in combined heat and power (CHP) systems. Modelling compares biomass cost and netback to analyse the feasibility of CHP systems, as well as the internal rate of return (IRR) and payback period (PBP). Models are implemented into the IMP Bio2Energy® software (Instituto Mexicano del Petróleo, Mexico City, Mexico) for practical application and demonstrated for bioenergy generation in the agroindustrial processes of tequila production, coffee and orange processing using as biomass the agave bagasse, coffee pulp and orange peels coproducts, respectively. Results show that the CHP systems are economically feasible, i.e., biomass cost of production is lower than netback, PBP between 3 and 4 years and IRR > 20%. The cost of bioenergy is lower than the cost of fuel oil and grid electricity being replaced. The sensitivity analysis for boiler steam pressure showed that there is an optimal pressure for coffee pulp (40 bar), a threshold pressure for orange (60 bar) and agave bagasse (70 bar). Sensitivity to biomass input indicated a maximum capacity where economy of scale does not produce any improvement in the indicators. Results demonstrate the usefulness of the modelling approach and IMP Bio2Energy® in analysing biomass CHP systems. [ABSTRACT FROM AUTHOR]

Samples of airborne particles with aerodynamic diameters smaller than 10 µm (PM10) were collected in 2021 at two households in the Metropolitan Area of Mexico City. Both sites are in areas with different characteristics (residential or industrial zones). Simultaneous sampling indoors and outdoors was carried out at the two locations, using low-volume samplers. The study aimed to determine the indoor and outdoor gravimetric mass and elemental concentrations, identify emitting sources and possible penetration towards the households enhanced by natural ventilation, and assess risks to human health due to inhalation, ingestion, and dermal absorption, through hazard quotients. Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Se, and Pb concentrations were measured with X-ray fluorescence. Mass concentrations were higher indoors than outdoors, and most elemental concentrations had similar values in both environments. Cluster analysis was applied to identify possible emitting sources. The results showed a strong penetration of geogenic and industrial emissions at the Iztapalapa site, while only particles of industrial origin entered the interior of the Tlalnepantla dwelling, in both cases caused by the natural ventilation of the households. Health risks due to exposure to particles containing Fe, Ni, Cu, Zn, and Mn are not significant, and Pb and Cr only pose a risk via ingestion for men and women, although for children, there is a risk due to ingestion of all these elements. [ABSTRACT FROM AUTHOR]

The project proposal for the Desierto de los Leones tunnels in the Poetas Highway in Mexico aims to improve the excavation and support systems and evaluate the safety levels during construction. The design is based on geological and geotechnical information from the original project and can be approached using various methods, including numerical simulations. The article includes a summary of the lithological characteristics, a reinterpretation of geotechnical properties, a description of new construction procedures, and the results of calculations using the finite data differences method. The proposed project aims to improve the safety and stability of the tunnels through advanced construction technologies and adapted procedures, generated by a redesign and the scientific application of new techniques developed for this project. [ABSTRACT FROM AUTHOR]

In the three major urban agglomerations in Mexico (Mexico City, Monterrey, and Guadalajara), a significant change to anthropogenic sources of air pollution happened in March–May 2020, when policies implemented to stop the spread of the COVID-19 virus in Mexico caused the reduction of some anthropogenic sources of air pollution. We study the effect of these significant changes to air pollution sources using satellite-retrieved aerosol optical depth (AOD) and particulate matter (PM10 and PM2.5) concentrations from ground stations. The Chow test was applied to study trend changes in PM concentrations from 1 January to 30 May 2020. The Mann–Whitney non-parametric test was then used to compare average PM concentrations in April and May pre-lockdown, during lockdown in 2020, and post-lockdown in 2021. The assessment was further performed by evaluating the exceedance of national air quality standard maxima. The trend analysis showed that PM10 concentrations were reduced during lockdown in Mexico City and Monterrey, whereas no change was found for PM10 in Guadalajara and PM2.5 in the three cities. Further analysis showed that in Mexico City and Guadalajara, average PM10 and PM2.5 concentrations decreased by 12% in April and May 2020. However, in Monterrey, average PM10 and PM2.5 concentrations increased by 2.76% and 11.07%, respectively, in April 2021 due to a severe drought that caused dry soils and dust around the city. The results of this research can be used to implement policies for reducing anthropogenic sources to improve the air quality in urban areas. [ABSTRACT FROM AUTHOR]

This article presents a classification tree with predictive and prescriptive capabilities for the management of ground fractures in a crowded suburb in Tláhuac, a municipality of Mexico City. The tree is trained with observations of fractures parametrized with basic geotechnical and geological variables and specifications of the urban environment where they manifest. With the trained tree, the complexity of the scenario affected by the subsidence phenomenon is cleared because the relations between parameters can be viewed easily. With the trained tree, the influence of stratigraphic arrangements (geotechnical properties), geological conditions, size of roads and inhabited units, and location of water-pumping infrastructure in the appearance and exacerbation of cracks in soils is recognized, and this offers citizens and government administrators the possibility of anticipating damages and working on programs for improving structures and foundations, including relocation programs for communities at risk. [ABSTRACT FROM AUTHOR]

Despite being perceived as a warm country, winters in the Central Mexican Plateau frequently reach temperatures below zero Celsius. Prolonged exposures to low temperatures resulting in heart and respiratory morbidities are estimated to be responsible for 50% of the reported illness in the plateau, attributable primarily to the design of homes ill-suited to extreme temperatures. Consequently, there is a growing need to ensure that dwellings provide adequate indoor thermal conditions in the region. Hence, on-site sensors were used to collect temperature and relative humidity data every five minutes in 26 living rooms in the Plateau for 11 months. From these data, a subsample was determined, resulting in dwelling-level thermal comfort and health surveys on 15 homes. Computer simulations were used to investigate whether the building itself could provide thermal comfort under different retrofitting scenarios. Multiple linear regression relating the Predicted Percentage Dissatisfaction (PPD) index to self-perceived health was undertaken. Both monitored and simulated results were matched against our underheating model, finding that 92% of the homes had cold indoor environments, some even during summer. High PPD and intense levels of underheating were positive predictors of higher self-reported health problems. More self-reported health problems were correlated with both lower life satisfaction and self-worth, and with subjects' use of more adaptive strategies against environmental dissatisfaction. Dynamic computer simulations suggested that indoor thermal environments could be improved by enforcing the non-utilised standard NOM-ENER-020, which recommends the addition of insulation on walls and roofs. These findings suggest that the cold environments within homes of the plateau influence the self-perceived physical and mental health of its population. Hence, the application of adequate measures, such as retrofitting homes with stronger standards than the existing NOM-ENER-020 are needed in place. [ABSTRACT FROM AUTHOR]

Walnut tree (Carya illinoensis (Wangenh.) K. Koch) is a plant species showing ecological, social, and economic importance in México. The objective was to determine biomass productivity and to characterize the raw material and biomass briquettes obtained from walnut thinning pruning. The variables evaluated were tree total height (TH), fresh biomass (FB) and dry biomass (DB) per hectare (kg ha−1). Briquettes were made by using the biomass obtained in both orchards. Laboratory tests for original biomass included moisture content (MC), ash content (AC), volatile matter (VM) and fixed carbon (FC), as well as high heating value (HHV). Briquette studies also included diameter (D), weight (W), length (L), volume (V), density (Ds), and HHV. The data were analyzed by using descriptive statistics and analysis of variance (ANOVA) under a completely randomized design with factorial arrangement. Thinning pruning in walnut orchards provides 12 kg tree−1 (998 kg ha−1) of dry biomass, with acceptable levels of AC ≤ 5%, FC (75 to 76%), VM (18.7 to 19.7%) and HHV (16.2 to 16.7 MJ kg−1). The briquette international quality standards were fulfilled: MC≤ 10%, AC ≤ 5% and HHV > 18 MJ kg−1. The integrated use of walnut residues reduces the management problems registered during nut production and the sustainable options to generate bioenergy will be expanded. [ABSTRACT FROM AUTHOR]

Indoor microbes are a key component of air contamination that causes human health risks. However, compared with the aquatic and soil environment, microbial diversity and taxonomic structure and composition in subway facility are not well characterized. This study tries to explore surface bacterial communities by using swabs collected from four global subway facilities, such as Busan, Boston, Mexico City, and Moscow using 16S rRNA gene amplicon sequencing. The alpha-diversities on bacterial communities were significantly different between Moscow and other samples, despite the different sample characteristics among Busan, Boston, Mexico City samples. For bacterial taxonomic composition, three phyla such as Actinobacteria (41.1%), Proteobacteria (27.7%), and Firmicutes (18.9%), were most dominant among all samples, indicating that there was no significance (p > 0.05). The subway station surface samples were mostly dominated by Gram-positive bacteria, including genera Corynebacterium, Staphylococcus, and Streptococcus. PCoA analysis also revealed that the Moscow bacterial communities were clearly separated from others. In addition, core genera were only shared 75 genera among all samples, but 486 genera were shared with three global stations, such as Busan, Boston and Mexico City. These results suggested that the human activity and geographical environment potentially affect the establishment of the bacterial community. Although this study provided basic information on surface bacterial communities in the subway system, there is a remaining unknown microbiome in the indoor air environment. Therefore, we consistently try to understand the indoor environment's microbial ecology in the subway system. [ABSTRACT FROM AUTHOR]

A collection of 482 tetraploid wheat accessions from the CIMMYT Germplasm Bank was screened in the greenhouse for resistance to leaf rust disease caused by the fungus Puccinia triticina E. The accessions were screened against two races CBG/BP and BBG/BP in the field at two locations: against race CBG/BP at the Norman E. Borlaug Experimental Station (CENEB) located in the Yaqui Valley in the northern state of Sonora in Mexico during the 2014–2015 growing season; and against race BBG/BP at CIMMYT headquarters in El Batan, Texcoco, in the state of Mexico in the summer of 2015. Among the accessions, 79 durum genotypes were identified, of which 68 continued demonstrating their resistance in the field (past the seedling stage) against the two leaf rust races. An additional set of 41 genotypes was susceptible at the seedling stage, but adult plant race-specific resistance was identified in the field. The 79 seedling-resistant genotypes were tested against 15 different leaf rust races at the seedling stage to measure the usefulness of their resistance in a breeding program. Among the 79 accessions tested, 35 were resistant to all races used in the tests. Two sample sources, CIMMYT (18/35) pre-breeding germplasm and Ethiopian landraces (17/35), showed seedling resistance to all races tested except for seven landraces from Ethiopia, which became susceptible to the Cirno race identified in 2017. [ABSTRACT FROM AUTHOR]

We propose a hydrodynamic simulation model to understand the piezometric operation of the Celaya Valley aquifer. The aquifer is located at the east of Guanajuato State in México. Our proposed model reproduces, under transitory conditions, the performance of the aquifer during the dry season from year 2015 to 2019 and the rainy season from year 2010 to 2015. The simulation was projected for the two seasons up to eleven years ahead and considering only three simulation scenarios (one should bear in mind that there are a number of different and interesting scenarios): trend, pump reduction and pump increase. In general terms, the model accurately reproduces the natural conditions of the aquifer. It is necessary to continue taking measures for the preservation of water; similarly, it is suggested to continue monitoring the aquifer piezometric levels to update the model based on data availability. [ABSTRACT FROM AUTHOR]

Simple Summary: In Mexico, smallholder farmers produce locally adapted maize varieties, generally called landraces, for food. They participate in the conservation of landraces by selecting and storing their seeds from one production cycle to another, but are facing challenges such as storage losses caused by insects (mainly Sitophilus zeamais and Prostephanus truncatus) and climate change. In the current study, the effectiveness of the conventional storage practices of farmers in the highlands of Mexico (polypropylene woven bags) in minimizing storage losses and maintaining seed germination was compared with hermetic storage technologies. After six and three months of storage, the percentage of insect damage and weight loss was highest in samples stored in polypropylene woven bags, reaching 61.4% and 23.4% after six months of storage. On the contrary, with hermetic technologies, storage losses were minimal, with maximums of 4.1% and 2.2% for insect damage and weight loss, respectively. Overall, the germination rate of samples stored in these airtight containers was greater than 90%. The results of this study demonstrate the potential of hermetic technologies in preserving the biodiversity of maize seed landraces and strengthening smallholders' food security. Smallholder farmers who grow maize landraces face important challenges to preserve their seed biodiversity from one season to another. This study was carried out in the central highlands of Mexico to compare the effectiveness of two seed storage practices—specifically, polypropylene woven bags (farmers' conventional practice) vs. hermetic containers—for minimizing seed losses and maintaining germination. Four Mexican landraces were stored for three and six months. Data on moisture content and kernel damage were collected at the beginning and the end of the storage period. Pest-free samples collected were also analyzed for seed germination. Moisture content was below 13% overall and was not significantly affected by storage technology or storage time. Samples from the polypropylene woven bags suffered significant damage from Sitophilus zeamais and Prostephanus truncatus, with the percentages of insect damage and weight loss reaching 61.4% and 23.4%, respectively. Losses were minimal in seed stored in hermetic containers, with a maximum insect damage of 4.1% and weight loss of 2.2%. Overall, the germination rate of samples stored in these airtight containers was greater than 90%. This study provides additional evidence on the effectiveness of hermetic containers at maintaining Mexican landraces' seed quantity and quality during storage in smallholder conditions in central Mexico. [ABSTRACT FROM AUTHOR]

Some of the effects of climate change may be related to a change in patterns of rainfall intensity or scarcity. Therefore, humanity is facing environmental challenges due to an increase in the occurrence and intensity of droughts. The forecast of droughts can be of great help when trying to reduce the adverse effects that the scarcity of water brings, particularly in agriculture. When evaluating the conditions of water scarcity, as well as in the identification and characterization of droughts, the use of predictive models of drought indices could be a very useful tool. In this research, the utility of Artificial Neural Networks with exogenous inputs was tested, with the aim of predicting the monthly Standardized Precipitation Index in 4 regions (Semi-desert, Highlands, Canyons and Mountains) of north-central México using predictor data from 1979 to 2014. The best model was found using the scaled conjugate gradient backpropagation algorithm as the optimization method and was set to the following architecture: 6-25-1 network. The correlation coefficient of predicted and observed Standardized Precipitation Index values for the test dataset was between 0.84 and 0.95. As a result, the Artificial Neural Network models performed successfully in predicting Standardized Precipitation Index at the four analyzed regions. The developed and tested Artificial Neural Network models in this research suggest remarkable prediction abilities of the monthly Standardized Precipitation Index in the study region. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) vaccines effectively protect against severe disease and death. However, the impact of the vaccine used, viral variants, and host factors on disease severity remain poorly understood. This work aimed to compare COVID-19 clinical presentations and outcomes in vaccinated and unvaccinated patients in Mexico City. From March to September 2021, clinical, demographic characteristics, and viral variants were obtained from 1014 individuals with a documented SARS-CoV-2 infection. We compared unvaccinated, partially vaccinated, and fully vaccinated patients, stratifying by age groups. We also fitted multivariate statistical models to evaluate the impact of vaccination status, SARS-CoV-2 lineages, vaccine types, and clinical parameters. Most hospitalized patients were unvaccinated. In patients over 61 years old, mortality was significantly higher in unvaccinated compared to fully vaccinated individuals. In patients aged 31 to 60 years, vaccinated patients were more likely to be outpatients (46%) than unvaccinated individuals (6.1%). We found immune disease and age above 61 years old to be risk factors, while full vaccination was found to be the most protective factor against in-hospital death. This study suggests that vaccination is essential to reduce mortality in a comorbid population such as that of Mexico. [ABSTRACT FROM AUTHOR]

Simple Summary: Epidemiological studies have identified associations between fine particulate matter (with an aerodynamic diameter of less than 2.5 μm (PM2.5)) and ozone exposure with cardiovascular disease; however, studies linking ambient air pollution and premature coronary artery disease (pCAD) in Latin America are nonexistent. We leveraged data from the Genetics of Atherosclerotic Disease (GEA) Mexican study to address the question of the extent to which long-term exposure to ozone and PM2.5 exposure was associated with the risk of pCAD. We showed for the first time a higher risk of pCAD associated with 1 ppb increase in ozone (1-year, 2-year, 3-year, and 5-year) and 5μg/m3 of PM2.5 (5-year) compared to controls. This study provides evidence that ozone and PM2.5 may be a modifiable risk factor for pCAD. (1) Background: Epidemiological studies have identified associations between fine particulate matter (PM2.5) and ozone exposure with cardiovascular disease; however, studies linking ambient air pollution and premature coronary artery disease (pCAD) in Latin America are non-existing. (2) Methods: Our study was a case–control analysis nested in the Genetics of Atherosclerotic Disease (GEA) Mexican study. We included 1615 participants (869 controls and 746 patients with pCAD), recruited at the Instituto Nacional de Cardiología Ignacio Chávez from June 2008 to January 2013. We defined pCAD as history of myocardial infarction, angioplasty, revascularization surgery or coronary stenosis > 50% diagnosed before age 55 in men and age 65 in women. Controls were healthy individuals without personal or family history of pCAD and with coronary artery calcification equal to zero. Hourly measurements of ozone and PM2.5 from the Atmospheric Monitoring System in Mexico City (SIMAT in Spanish; Sistema de Monitero Atmosférico de la Ciudad de México) were used to calculate annual exposure to ozone and PM2.5 in the study participants. (3) Results: Each ppb increase in ozone at 1-year, 2-year, 3-year and 5-year averages was significantly associated with increased odds (OR = 1.10; 95% CI: 1.03–1.18; OR = 1.17; 95% CI: 1.05–1.30; OR = 1.18; 95% CI: 1.05–1.33, and OR = 1.13; 95% CI: 1.04–1.23, respectively) of pCAD. We observed higher risk of pCAD for each 5 µg/m3 increase only for the 5-year average of PM2.5 exposure (OR = 2.75; 95% CI: 1.47–5.16), compared to controls. (4) Conclusions: Ozone exposure at different time points and PM2.5 exposure at 5 years were associated with increased odds of pCAD. Our results highlight the importance of reducing long-term exposure to ambient air pollution levels to reduce the burden of cardiovascular disease in Mexico City and other metropolitan areas. [ABSTRACT FROM AUTHOR]

Sticky Platelet Syndrome (SPS) is a disorder characterized by platelet hyperaggregability, diagnosed by studying in vitro platelet aggregation with ADP and epinephrine. It is the second most common cause of thrombophilia in Mexican Mestizos and manifests as an autosomal dominant trait which, combined with other coagulopathies, contributes significantly to the morbidity and mortality of patients with primary thrombophilia. It is easily treatable with antiplatelet drugs; however, the methods for diagnosis are not readily available in all clinical laboratories and the disorder is often overlooked by most clinicians. Herein, we present the results of more than 20 years of Mexican experience with the study of SPS in a Mestizo population. [ABSTRACT FROM AUTHOR]

Plant roots recruit most prokaryotic members of their root microbiota from the locally available inoculum, but knowledge on the contribution of native microorganisms to the root microbiota of crops in native versus non-native areas remains scarce. We grew common bean (Phaseolus vulgaris) at a field site in its centre of domestication to characterise rhizosphere and endosphere bacterial communities at the vegetative, flowering, and pod filling stage. 16S r RNA gene amplicon sequencing of ten samples yielded 9,401,757 reads, of which 8,344,070 were assigned to 17,352 operational taxonomic units (OTUs). Rhizosphere communities were four times more diverse than in the endosphere and dominated by Actinobacteria, Bacteroidetes, Crenarchaeota, and Proteobacteria (endosphere: 99% Proteobacteria). We also detected high abundances of Gemmatimonadetes (6%), Chloroflexi (4%), and the archaeal phylum Thaumarchaeota (Candidatus Nitrososphaera: 11.5%): taxa less frequently reported from common bean rhizosphere. Among 154 OTUs with different abundances between vegetative and flowering stage, we detected increased read numbers of Chryseobacterium in the endosphere and a 40-fold increase in the abundances of OTUs classified as Rhizobium and Aeromonas (equivalent to 1.5% and over 6% of all reads in the rhizosphere). Our results indicate that bean recruits specific taxa into its microbiome when growing 'at home'. [ABSTRACT FROM AUTHOR]

A volcanic eruption can produce large ash clouds in the atmosphere around a volcano, affecting commercial aviation use of the airspace around the volcano. Encountering these ash clouds can cause severe damage to different parts of the aircraft, mainly the engines. This work seeks to contribute to the development of methods for observing the dispersion of volcanic ash and to complement computational methods that are currently used for the prediction of ash dispersion. The method presented here is based on the frequency of occurrence of the regions of airspace areas affected by ash emission during a volcanic eruption. Popocatepetl volcano, 60 km east of Mexico City is taken as a case study. A temporal wind analysis was carried out at different atmospheric levels, to identify the direction towards which the wind disperses ash at different times of the year. This information showed two different trends, related to seasons in the direction of dispersion: the first from November to May and the second from July to September. To identify the ash cloud and estimate its area, a set of 920 MODIS images that recorded Popocatepetl volcanic activity between 2000 and 2021 was used. These satellite images were subjected to a semi-automatic, digital pre-processing of binarization by thresholds, according to the level of the brightness temperature difference between band 31 (11 µm) and band 32 (12 µm), followed by manual evaluation of each binarized image. With the information obtained by the processing of the MODIS image, an information table was built with the geographical position of each pixel characterized by the presence of ash for each event. With these data, the areas around Popocatepetl volcano with the highest frequency of affectation by ash emissions were identified during the period analyzed. This study seeks to complement the results obtained by numerical models that make forecasts of ash dispersions and that are very important for the prevention of air navigation risks. [ABSTRACT FROM AUTHOR]

The Mexico City Metropolitan Area, located within the Mexico Basin, is the most important economic center in Mexico. An ever-growing population, currently at 22 million with increasing water demands, has resulted in the overexploitation of groundwater with associated impacts to hydrological conditions for a century. Land subsidence due to chronic groundwater level declines has damaged infrastructure and increased water delivery and flood control challenges, causing loss of aquifer storage. An additional associated problem is groundwater quality deterioration, which reduces potable supplies due to increasing anthropogenic pollution and salinization. A new integrated conceptual model of the Mexico Basin Aquifer has been constructed based on a comprehensive compilation of existing and new hydrogeological knowledge. As a result, this conceptual model updates and improves the understanding of the characteristics of the aquifer and current hydrodynamic behavior of groundwater. Four hydrogeological units were identified, their heads and related flow system interdependencies were evaluated and their hydraulic properties associated; this allowed identifying local, intermediate and regional flow systems, aquifer transition from confined to unconfined conditions, changes to land subsidence and groundwater quality deterioration. This conceptual model could be the basis in building a numerical model, and as a powerful tool to test different management scenarios for decision-making. [ABSTRACT FROM AUTHOR]

This study analyzes 50 annual climate change indices related to temperature and precipitation in the Valley of Mexico basin for the period 1951–2010. First, a quality and homogenization analysis of 90 weather stations (categorized as urban, suburban, and rural) in the basin was performed using the Climatol algorithm. The non-parametric Mann–Kendall test and the Sen's slope method were applied to determine the existence of a trend and to estimate the magnitude of the change in extreme climate indices, respectively. To eliminate the serial correlation problem, the lag-1 method and the Patakamuri tests were used. Statistically significant positive trends were found for SU, TMm, TNm, TNn, TX90p, and WSDI, as well as negative ones for FD, TX10p, TN10p, CSDI, and HDDheat18. The results seem to support an influence of anthropogenic global warming on the study region, rather than local effects of urbanization. However, it is likely that some significant differences in the urban change rate of some indices could be due to local effects, such as the difference in land cover that occurs between urban and rural stations. Not enough statistically significant results were found for the climate change indices related to precipitation in most of the stations. Compared to other studies in the Mexico City area, the main contribution of this study is the analysis of 50 climate indices in a 60-year period working with a quality-controlled and homogenized database. [ABSTRACT FROM AUTHOR]