Case Study In Mexico Research Articles

Comparative Reflections on the Acquisition of Language in Hearing and Deaf Children: A Case of Natural Learning of Mexican Sign Language

Sign languages are visual and iconic languages used by Deaf communities worldwide. Sign language develops from the linguistic stimulus in the visuo-gestural modality, unlike hearing children who receive the stimulus in the auditory-vocal modality. This paper presents one case study in Mexico where deaf children naturally acquire Mexican Sign Language (LSM). Deaf children can access and develop sign language if the immediate context offers ways parallel to oral language development. Universal Grammar and biolinguistics support the natural process of the acquisition of languages.

Medium-Term Hydrothermal Scheduling of the Infiernillo Reservoir Using Stochastic Dual Dynamic Programming (SDDP): A Case Study in Mexico

This article aims to obtain and evaluate medium-term operating policies for the hydrothermal scheduling problem by using the stochastic dual dynamic programming (SDDP) approach. To this end, to feed the mathematical model and build the probability distribution functions that best fit each month of the actual inflow volume, monthly inflow data recorded from 1938 to 2018 for the Infiernillo reservoir located in Mexico were employed. Moreover, we simulated inflow volume scenarios using the Monte Carlo method for each month of a one-year planning period. The SDDP approach to solving the optimization problem consisted of the simulation of one forward scenario per iteration and the stabilization of the total operating cost as a convergence criterion, which results in an operating policy. We then assessed its quality by estimating the one-sided optimality gap. It is worth mentioning that the best operation policy required scenario trees of up to 17,000 inflow realizations per stage. Additionally, to study the evolution of the expected value along the planning horizon of the main variables involved in the medium-term hydrothermal scheduling problem, we simulated the best operation policy over 10,000 inflow scenarios. Finally, to show the practical value of the proposed approach, we report its computational complexity.

Forge ahead in acquisition and model building via full-waveform inversion: Gulf of Mexico case study

Full-waveform inversion (FWI) has proven itself an essential tool for velocity model building using seismic data. In recent years, the geophysical community has made substantial progress in developing FWI to overcome some long-standing limitations, such as handling cycle skipping, better using reflection energy, including more physics in the inversion algorithms, and increasing inverted frequencies to achieve higher resolution. FWI does not only target the larger and midscale model updates, more and more FWI examples were presented with increased resolution which allows for extraction of FWI derived reflectivity. Interrogating the FWI kernel with given geology and acquisition geometry can provide critical information on how the acquisition design should be optimized to provide FWI a better opportunity to update the velocity model at target depth, especially in the deep part of the model. When the acquisition geometry is different in terms of offsets, azimuthal coverage, and the minimum frequency in the recording, it can be analyzed to design workflows to enable FWI to optimally update the model parameters. Obviously, recent ocean-bottom node acquisitions that record long offsets, full azimuth, and low frequencies have made FWI shine in the seismic industry. Modifying and reshaping a complex salt geometry is one of the ultimate goals of FWI. In addition to the salt boundary being an issue, there is a potential cycle-skipping problem associated with uncertainties of large salt bodies missing or misplaced even though the frequencies used to start FWI are becoming lower due to the advancement in seismic acquisition and FWI algorithms. Furthermore, if the FWI-predicted data are simulated with an acoustic engine, it could pose amplitude and phase discrepancies at high-velocity contrast interfaces. Elastic FWI alone has been proposed as a means of overcoming these challenges associated with salt and regions with high-velocity contrast. We determine the FWI progress of the past few decades with the latest examples from different acquisition geometries.

Feminism and Folk Art: Case Studies in Mexico, New Zealand, Japan, and Brazil

Feminism and Folk Art: Case Studies in Mexico, New Zealand, Japan, and Brazil

GHG Emission Accounting and Reduction Strategies in the Academic Sector: A Case Study in Mexico

The carbon footprint (CF) quantifies the greenhouse gas (GHG) emissions generated by human activities, expressed in carbon dioxide equivalent (CO2e) units. It is an instrument for monitoring and mitigating the effects of climate change, which particularly affects low- and middle-income countries such as Mexico. The Mexican government has established a goal of reducing GHG emissions by 22% from the levels in 2000 by 2030. Although most efforts to reduce GHG emissions have been focused on the energy and agriculture sectors, the academic sector is also important since it can advise changes in public policy. In this study, the 2019 CF of the Centro Roberto Garza Sada (CRGS), a design school at the Universidad de Monterrey, was estimated in an effort to develop measures for reducing GHG emissions. The GHG Protocol was employed to calculate the total CF of the CRGS and identify the greatest contributors, including commuting (50.2%), energy purchase (28.5%), business travel (19.6%), and energy generation, use of paper, refrigerants, and shipments (1.7%). Three progressive mitigation scenarios were developed to reduce the GHG emissions from commuting, energy consumption, collaborators and student mobility, and material resources. These strategies could reduce the GHG emissions of the CRGS by 63.5% of the baseline assessed.

Influence of Mixed Conifer Forest Thinning and Prescribed Fire on Soil Temperature and Moisture Dynamics in Proximity to Forest Logs: A Case Study in New Mexico, USA

Forest management activities often include fuels reduction through mechanized thinning followed by prescribed fire to remove slash. Management prescriptions may include the retention of logs for wildlife habitat and microsites for enhanced tree regeneration. We examined aboveground microclimate and belowground soil temperature and volumetric water content (VWC) dynamics beneath and adjacent to logs at 10, 20, and 30 cm depths in a mixed conifer forest. We assessed the soil variables over 7 years during pre-treatment, post-thinning, and post-fire using a Before–After/Control–Impact experimental design. We found that thinning and burning caused large increases in solar radiation and mean and maximum wind speeds, but only small changes in air temperature and humidity. The treatments increased the soil temperatures beneath the logs by up to 2.7 °C during spring, summer, and fall; the soil VWC increased from 0.05 to 0.08 m3/m3 year-round at 20 and 30 cm depths. Microsites 1–2 m away from the logs also showed soil temperature increases of up to 3.6 °C in spring, summer, and fall, while the measurements of the soil VWC produced variable results (moderate increases and decreases). The increased VWC in late winter/spring likely resulted from reduced plant transpiration and greater snow amounts reaching the ground without being intercepted by the forest canopy. Log retention on thinned and burned sites provided microsites with increased soil temperature and moisture in the top 30 cm, which can enhance soil ecosystem processes and provide refugia for invertebrate and vertebrate wildlife.

Sustainability framework of intelligent social houses with a synergy of double-façade architecture and active air conditioning systems

Social houses are built around the world to fulfill the basic needs of the growing population, especially middle-income families. Owing to the low budget available for such houses around the globe, necessary energy codes are often compromised. This research, through a methodological sustainability framework, presents the case study of Mexico with the objective to address this worldwide issue. More than 100,000 social houses were built in Mexico just in the year 2021 without strictly following any definitive building energy codes. Eventually, this is a ticking bomb, if left unaddressed, that can bring serious energy and environmental consequences connected with various social issues. Thus, as a research gap, the conventional 4E (energy, exergy, economic, and environmental) analysis cannot fully address such a complex energy-environmental-economic-social nexus. This work proposes an integrated sustainability framework of the practicability of the bioclimatic architecture of such a social house including energy, economic, environmental, and social assessment (novel addition to the analysis). The novel methodology is implemented on a novel technological advancement where double-façade architecture (i.e., solar chimney) is installed through a synergy and intelligent operation with an active air conditioning system including a desiccant enhanced air cooler and novel dew-point evaporative cooler. The article makes use of conventional physics-based modeling of thermal machines combined with an artificial neural network digital twin-based data-driven non-sorting genetic optimization of solar chimneys for various climatic conditions of Mexico. The optimal points are evaluated using annual climatic data to maintain the thermal comfort conditions and the results have suggested an increase of ∼48% through intelligent integration of double-façade architecture with the Maisotsenko cycle air cooler. Life-cycle economic assessment has suggested the Levelized cost of air conditioning be between 0.0096 and 0.0390 USD/kWh and can save up to ∼273 MXN per month with a real payback period of ∼8 years. Environment assessment has reported mitigation of up to ∼5668.59 kgCO2/year as compared to conventional vapor compression refrigeration systems. The social assessment is conducted on a pilot scale to directly ask the people of Mexico about their perception of the installation of the solar chimney while giving the fact that the initial price of the social houses can increase between 2.5 and 4%. It is reported that ∼62% of the sample is willing to install it even with a high price tag with a motive to initiate the climate change mitigation phenomena. The importance of the work has concluded that the government needs to take drastic and tough decisions to further regulate the energy efficiency in the social houses and limit the constructors to offer sustainable building construction.

Analytic deliberation approach for collaborative determination of impact significance of projects in dispute, a case study in Mexico

The determination of impact significance is a critical step in Environmental Impact Assessment (EIA). Yet, the notion of impact significance is inherently subjective, immersed in uncertainty, and influenced by competing interests. This article addresses the difficult task of collaboratively determining the significance of the environmental impacts of projects in dispute. We introduce an approach centered on analytic deliberation that entails three steps: analysis, translation, and deliberation. Analysis combines and synthesizes impact significance into a single index using a fuzzy pattern classification algorithm, which also integrates the inherent uncertainty of impact assessment. Translation transforms the index into understandable and accessible spatial representations through geovisualization. Deliberation promotes safe spaces for collaboration in which stakeholders examine evidence openly and reflect on the conflicting values underlying their perspectives. The outcome of the approach is a compromise on the most meaningful representation of impact significance, if one exists, as the basis for agreement on the appropriate prevention, mitigation, and compensation measures of a project. Hence, it helps to reach agreement on the impact prevention, mitigation, and compensation strategy prior to the consultation process required by law in most countries. We illustrate our approach through an example from Mexico.

Incorporating deep learning predictions to assess the water-energy-food nexus security

Water, energy and food (WEF) are experiencing significant stress due to an increase in their demand and scarcity, and this situation will worsen in the coming years. For this reason, this paper proposes a WEF nexus index, which consists of 6 indicators of availability and accessibility to measure water, energy and food security. The proposed methodology, based on indicators and a scoring system, allows decision-makers to evaluate the nexus security and implement actions to achieve the sustainability of the three resources by 2050. Models based on deep learning are developed for the projection of the production and consumption of resources for the case study of Mexico. The Long Short-Term Memory and Gated Recurrent Unit networks are considered. Projections for 2050 resulted in water consumption of 121,679 hm3, electricity generation of 772,486 GWh and electricity consumption of 932,764 GWh, while food production will reach 351,802,080 tons. This represents an increase of 51.7% in water consumption, 180.33% in electricity generation, 254.54% in electricity demand and 103.05% in food production, compared to 2010. The WEF nexus index has an upward trend because the accessibility of water and energy will increase by 2050, but their availability will decrease; the opposite is the case in the food sector, where availability will increase and access will decrease.

Strategic planning for the optimal distribution of COVID-19 vaccines

This work presents a multi-objective optimization strategy for fair vaccine allocation through different fairness schemes. The proposed approach considers a diverse series of parameters related to different public health data and social behaviors that influence the correct distribution of vaccines, such as corruption and crime. Simultaneously, the formulation includes prioritizing those groups with the highest risk based on the epidemiological traffic light. Furthermore, the presented strategy involves different budget constraints that allow identifying trade-off solutions through Pareto fronts. Therefore, vaccine allocations are obtained by combining fairness concepts with multi-objective optimization. The applicability of the model is illustrated using the case study of Mexico. The solution to the proposed scenarios was carried out using different justice schemes and an economic objective function. The results show the compromises between a satisfaction index and costs, which are shown through Pareto optimal solutions that allow selecting the solutions that balance the objectives. The solutions provided by the social welfare scheme suggest a greater allocation of vaccines to those states with higher epidemiological risk, which may be helpful in the first stage of vaccination. On the other hand, the Rawlsian scheme provides more balanced solutions that can be useful in situations with lower rates of infection. Finally, the Nash scheme is the one that provides the most balanced solutions, favoring to a lesser extent the areas with the highest epidemiological risk, which may be useful in the later stages of vaccination.

Tropical Dry Forest Dynamics Explained by Topographic and Anthropogenic Factors: A Case Study in Mexico

Tropical dry forest is one of the most threatened ecosystems, and it is disappearing at an alarming rate. Shifting cultivation is commonly cited as a driver of tropical dry forest loss, although it helps to maintain the forest coverage but with less density. We investigated tropical dry forest dynamics and their contributing factors to find out if there is an equilibrium between these two processes. We classified multi-temporal Sentinel-2A images with machine learning algorithms and used a logistic regression model to associate topographic, anthropogenic, and land tenure variables as plausible factors in the dynamics. We carried out an accuracy assessment of the detected changes in loss and gain considering the imbalance in area proportion between the change classes and the persistence classes. We estimated a 1.4% annual loss rate and a 0.7% annual gain rate in tropical dry forest and found that the topographic variable of slope and the anthropogenic variable of distance to roads helped explain the occurrence probability of both tropical forest loss and tropical forest gain. Since the area estimation yielded a wide confidence interval for both tropical forest loss and gain despite the measures that we took to counterbalance the disproportion in areas, we cannot conclude that the loss process was more intense than the gain process, but rather that there was an equilibrium in tropical dry forest dynamics under the influence of shifting cultivation.

Application of full-waveform inversion to land data: Case studies in onshore Mexico

Velocity model building and imaging for land surveys are often challenging due to near-surface complexity contaminating the reflection signal. Incorporating full-waveform inversion (FWI) in the velocity model building workflow for land surveys offers benefits not achieved with traditional model building tools, but it also brings difficulties. We have developed an effective model building workflow for land seismic data that incorporates dynamic matching FWI (DMFWI). DMFWI employs an objective function that uses multidimensional local windowed crosscorrelations between the dynamically matched version of observed and synthetic data. Dynamic matching de-emphasizes the impact of amplitudes, allowing the algorithm to focus on using kinematic information for velocity updates. The proposed workflow produces a geologically plausible and consistent model for data acquired with limited offsets. Refraction and reflection tomography may also be included in the workflow. The workflow is applied to onshore surveys in Mexico. Despite challenges of the near-surface geology and limitations of the acquisition parameters in the study areas, the proposed model building workflow successfully derives a high-resolution velocity model that significantly improves the migrated depth image.

Uloga države u izgradnji održivog nacionalnog identiteta - studija slučaja Meksiko

This research investigates the national identity building process and corresponding role of the state in it. In many societies, states monopolised entire process, yet success they have been achieving is ambiguous. Using the Mexico case study, the research explores prospects of the state to lead the process of building a stable and sustainable national identity. To respond to the research question, authors analyse role of the Mexican state and ruling regimes in the process of different narratives production and parallelly investigates structural, historically conditioned factors. The conclusion is that the state cannot compensate authenticity and stability of the national identities which arise independently through the longue durée processes by producing and imposing artificial discourses and ideas.

Contextual challenges for implementing strategic environmental assessment in the Global South: insights from a case study in Mexico

ABSTRACT An increasing number of countries are implementing strategic environmental assessment (SEA) to support the development of environmentally sustainable policies, plans and programs. However, some Global South countries are yet to legislate for SEA and research is needed to understand the contextual challenges to implementing SEA effectively in these jurisdictions. Here, we examine Mexico’s first attempt at applying SEA to assess the potential impacts of urban development plans on a city-wide scale, including those on biodiversity and ecosystem services. Using stakeholder interviews and reflexive thematic analysis, we identify and discuss key factors to consider when formally implementing SEA in Mexico for it to achieve its intended objectives. We relate our findings to existing studies on SEA in Global South countries and discuss contextual challenges that may be shared by these jurisdictions, namely: limited knowledge and experience with SEA, low trust in public institutions, and limited institutional capacity of environmental agencies. We then provide recommendations for addressing these shared challenges, which may also prove useful for countries experiencing difficulties with the application of SEA.

A LiDAR-based geopedologic approach to address pre-Hispanic agricultural landscapes in Northern Michoacán, West Mexico

The methodical exploitation of arable lands in pre-Hispanic Mesoamerica has been recognized since the 16th century, but the Spanish Conquest caused cultivated landscapes to be dramatically modified. Thus, general amazement remains great when remote sensing techniques (RS) like airborne laser scanning (LiDAR) uncover fossilized farmlands. Recent studies demonstrated that agrarian features are widespread among the remains revealed by LiDAR-derived models. Efforts are being made to map these features but few studies have focused directly on the landforms and soils which they modify. Concurrently, while paleopedology has refined the identification of anthropogenic features within soils, spatial approaches correlating soil covers and archaeological sites have received less attention as perspectives often diverge between archaeological mapping, which often focuses on intra-site elements, and soil mapping, which generally encompasses broader areas. Yet, geoscientists have used RS to predict soil parameters and demonstrated that it could increase accuracy in knowledge-based soil maps. Today, while LiDAR-derived data are facilitating archaeological mapping beyond settlement limits, high-resolution RS also offers opportunities for more accurate soil mapping and calls for harmonization of perspectives. We present a method that combines LiDAR-based RS and fieldwork in archaeology and soil science to address pre-Hispanic cultivated landscapes based on a case study in West Mexico. It focuses on the Zacapu area, where long-lasting archaeological and geoecological research offered a solid background. We used LiDAR visualizations, modeling, and satellite images to detect anthropogenic and geopedologic features. The latter was verified through field surveys and test pits. Archaeological material and soil analyses followed. All data were mapped on GIS. As a result, we were able to update and improve significantly both the archaeological and geopedologic maps. The approach further provided an unprecedented reconstruction of landscape appropriation from the 6th to the 15th century AD. It demonstrates that archaeology, geomorphology, and pedology can efficiently complete each other to address more comprehensively pre-Hispanic cultivated landscapes.

Mobile TV: where we are and where we are going

The article presents (1) the technical characteristics of Mobile TV [Mobile TV] and how it differs from IPTV and Internet TV [Internet TV], (2) network, spectrum and equipment issues that will influence the regulatory framework, (3) the opportunities created for Mobile TV when migrating to digital TV, and (4) a case study in Mexico concerning the regulatory framework for telecommunications and broadcasting services, market players, spectrum availability, migration to digital TV and other issues prominent for Mobile TV

Photovoltaic Power Generation Forecasting for Regional Assessment Using Machine Learning

Solar energy currently plays a significant role in supplying clean and renewable electric energy worldwide. Harnessing solar energy through PV plants requires problems such as site selection to be solved, for which long-term solar resource assessment and photovoltaic energy forecasting are fundamental issues. This paper proposes a fast-track methodology to address these two critical requirements when exploring a vast area to locate, in a first approximation, potential sites to build PV plants. This methodology retrieves solar radiation and temperature data from free access databases for the arbitrary division of the region of interest into land cells. Data clustering and probability techniques were then used to obtain the mean daily solar radiation per month per cell, and cells are clustered by radiation level into regions with similar solar resources, mapped monthly. Simultaneously, temperature probabilities are determined per cell and mapped. Then, PV energy is calculated, including heat losses. Finally, PV energy forecasting is accomplished by constructing the P50 and P95 estimations of the mean yearly PV energy. A case study in Mexico fully demonstrates the methodology using hourly data from 2000 to 2020 from NSRDB. The proposed methodology is validated by comparison with actual PV plant generation throughout the country.

Barriers and bridges on water management in rural Mexico: from water-quality monitoring to water management at the community level.

Access to sufficient water of suitable quality represents a challenge for achieving several dimensions of sustainable development. Currently, water access is restricted to three of 10 persons globally. In rural areas of Mexico and other low-income countries, coverage could be even less due to the absence of formal supply; thus, rural communities usually perform water management. Surrounding community-based water management, various socio-ecological interactions emerge that determine access to water. Access to water will depend on the obstacles or capacities that arise within the socio-ecological system in which the community is immersed. This work identifies barriers and bridges to water access in a rural environment through mixed methods. The article draws on three case studies in southeastern Mexico by analyzing 90 questionnaires conducted at the household level and three focus groups in parallel with water quality analysis and its relationship with management practices. The barriers and bridges were classified into six water access challenges: (i) access to water in a sufficient quantity, (ii) access to water of adequate quality, (iii) access to water for household crop irrigation, (iv) hygiene and sanitation facilities, (v) collective organization, and (vi) climate variability. The main findings indicate that households’ water quantity and quality show deficiencies due to the lack of formal infrastructure and represent a health risk. Water fetching has the highest impact on women and children in poor rural areas, and it is a significant barrier to sustainable development. In contrast, the collective organization proved to be an essential bridge for water access in these communities.

A systematic approach for assessing water, energy and food security during the COVID-19 pandemic: case study of Mexico.

Assessing the security of the water–energy–food nexus is a topic of great importance, which allows determining the situation of each resource to implement actions for sustainable management of these resources in today's society. For this reason, a systematic procedure is proposed to evaluate the synergies of the water–energy–food nexus in a large region that is divided into subregions that allow considering their interactions. The new procedure considers the availability, accessibility and regional interdependence of resources while annexing economic and social aspects. A composite index called the WEF Global Index is developed, which involves the WEF nexus index and has nine indicators that evaluate the availability, accessibility and regional interdependence of each resource in the water–energy–food nexus. This new index considers the Gross Domestic Product per capita and the involved population. As a case study, the 32 states of Mexico were considered to assess the effects of the COVID-19 pandemic on the economy and the security of the water-energy-food nexus at the state level. For this, the composite index was evaluated in the years 2019 and 2020. The results show that from 2019 to 2020, the value of the global index increased in 13 states, in 21 states the security index of the WEF nexus increased, and in 9 states the GDP per capita index increased. On the other hand, the results indicate that in 11 states there was no improvement in the nexus security index due to the increase in water demand, which considerably affected the water availability indicator.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10668-022-02671-2.

A Call for Biomonitoring Systems in Latin America and the Caribbean: Considerations for Potentially Toxic Metals/Metalloids.

The Latin America and the Caribbean (LAC) region makes up 8.4% of the world’s population. Human biomonitoring (HBM) programs, which can shed light on population-level exposure to environmental contaminants such as toxic metals and thus, improve the health of the populations are inexistent in LAC countries. We call for the creation of HBM programs in the region and identify three viable design options for HBM at the individual level, through national surveys, newborn blood collection, and biobanks. We highlight some of challenges to the implementation of HBM programs, including financial and human resources, technical constrains (laboratory), sample, and data logistics. Finally, we provide the case studies of Brazil, Chile, Mexico, and Uruguay, to illustrate a range of responses to toxic metal exposure in non-occupational populations. Although different in many respects, the individual country responses share two commonalities: 1) academic centers drive the research to raise awareness of governmental entities; 2) reference levels are adapted from international norms rather than arising from the studied populations. Well-designed and sufficiently funded biomonitoring systems need to be established in each country of the LAC region. HBM programs are key to promoting human health by informing the public and contributing to policy processes that establish sustainable environmental controls and health prevention programs.