Case Study In Mexico Research Articles

Technology-based entrepreneurial opportunity discovery and development

Technology-based entrepreneurs in Latin America face different institutional environments and have less access to knowledge and resources than those in industrialized economies. Opportunity discovery and construction therefore follow also different paths. Results from a set of parallel case studies in Argentina, Colombia and Mexico, explore some differences in terms of the role of available technological and market knowledge, and in terms of the entrepreneur’s background. But also, strong similarities among these countries’ economic development, their R&D infrastructure, and their institutional environments, shape similar patterns in their entrepreneurs’ endeavours. These patterns have important public policy implications for promoting innovation in transitional economies.

Assessing the relationship between vegetation greenness and surface temperature through Granger causality and Impulse-Response coefficients: a case study in Mexico

ABSTRACTThe existence of a consistent inverse relationship between vegetation greenness and surface temperature has been the premise of many environmental studies. However, some authors have found that the nature of this relationship varies depending on the spatial and temporal scales of analysis as well as vegetation type. Therefore, this research aims to contribute to the understanding of this matter by evaluating the annual and intra-seasonal relationship between Leaf Area Index (LAI) and Land Surface Temperature (LST) in Central Mexico using monthly anomalies of Moderate Resolution Imaging Spectroradiometer (MODIS) data collected from 2002 to 2017. LAI is proposed as an alternative index to overcome the shortcomings of other widely used indicators of vegetation greenness (e.g. Normalized Difference Vegetation Index and Enhanced Vegetation Index). The presence/absence of any relationship is investigated through the notion of Granger causality, while the sign and strength of the relationship is estimated by means of an Impulse-Response (IR) function. Unlike traditional regression and correlation analysis, the Granger causality approach enables the examination of lagged effects of one variable over the other based on past values of both variables. IR coefficients, which have been rarely used in the related literature, help to model the over-time response of a variable with the change of another variable. The overall results indicate that, at any temporal scale, Granger causality from LST to LAI occurs more consistently than causality in the opposite direction. At the annual scale, the nature of the relationship is primarily inverse in both directions and usually weaker from LAI to LST. At the seasonal scale, the occurrence of LST to LAI causality is higher in spring (it occurs in about 40% of the evaluated pixels) and lower in winter (10%) among all forest types. The effect of LST on LAI is predominantly inverse (median coefficient 1 month after impulse −0.043) and particularly strong in deciduous broadleaf forest during summer. On the other hand, the effect of LAI on LST is mainly direct in autumn and inverse in the remaining seasons, except for evergreen needleleaf forest where the effect is inverse only in summer. The highest presence (23%) and strength (−0.039) of LAI to LST causality occur in spring over deciduous broadleaf forest. Based on these results, caution has to be exercised when assuming a consistent strong inverse relationship between vegetation greenness and surface temperature, which seems to be the general consensus in much of the literature that makes use of these two variables to study an environmental phenomenon.

Climate Security as a Legislative Framework: A Case Study in Mexico

Climate Security as a Legislative Framework: A Case Study in Mexico

The problem of pseudo-STEM programs in higher education: A classification criterion

Most of the indicators for STEM programs in higher education such as the number of programs and students enrolled depend on what is considered as a STEM program. Currently, each country develops its own STEM indicators, without establishing comparable criteria across countries for the selection of the programs considered STEM, which make it difficult for a correct comparison between countries. Despite this, the OECD publishes comparative reports on the state of STEM higher education among its member countries. The OECD develops these reports with data provided by each country; that is, each country decides the mechanisms to produce the data. This paper proposes a selection criterion of STEM programs to generate internationally comparable data. This work obtains the selection criterion through a conceptual and contextual socio-historical review of the STEM movement. This work conducts an exploratory case study in Mexico from 2011 to 2017 to show the discrepancy in STEM higher education indicators when using different selection criteria. The results show that 60% of the programs classified as STEM, do not meet the classification criteria established. Also, that 60 % of misclassified programs have a higher curricular content of administrative or social subjects, but in their name includes words that refer to STEM fields. The authors call these programs as Management-STEM (MSTEM).

A Multi-Stage Machine Learning Approach to Predict Dengue Incidence: A Case Study in Mexico

The mosquito-borne dengue fever is a major public health problem in tropical countries, where it is strongly conditioned by climate factors such as temperature. In this paper, we formulate a holistic machine learning strategy to analyze the temporal dynamics of temperature and dengue data and use this knowledge to produce accurate predictions of dengue, based on temperature on an annual scale. The temporal dynamics are extracted from historical data by utilizing a novel multi-stage combination of auto-encoding, window-based data representation and trend-based temporal clustering. The prediction is performed with a trend association-based nearest neighbour predictor. The effectiveness of the proposed strategy is evaluated in a case study that comprises the number of dengue and dengue hemorrhagic fever cases collected over the period 1985-2010 in 32 federal states of Mexico. The empirical study proves the viability of the proposed strategy and confirms that it outperforms various state-of-the-art competitor methods formulated both in regression and in time series forecasting analysis.

Ex-ante deference and reparations, the case studies of Colombia and Mexico

Usually analyses of deference consider courts’ review of past agency action. Governments interpret in a specific manner a norm or regulation and the judge decides the lawfulness of that interpretation after the fact. However, judges analyze governments’ future decisions as well, for example in granting reparations for human rights violations. Such decisions generally engage in an analysis of future actions that the government should perform in order to redeem victims and guarantee the violation will not recur. The underpinning principle of judicial deference is that a court should not attempt to second guess or substitute its judgment for the judgment of another decision maker, nor should it opine on the wisdom of a policy or law. With respect to human rights violations, a more deferential approach might let the government determine what measures it will take by way of reparations and prevention of recurrence, while a non-deferential approach would spell out such measures in detail. Examining cases in Colombia and Mexico issued during the past 10 years, in this paper I argue that domestic courts have been granting reparations in a less deferential manner over time. This trend is very clear when analyzing non-repetition measures granted in these countries which include attempts to oblige governments to issue laws, reduce sanctions, and prohibit the transit of specific streets.

Lessons Learned from Rural Electrification Experiences with Third Generation Solar Home Systems in Latin America: Case Studies in Peru, Mexico, and Bolivia

There are 17 million people without access to electricity services in Latin America. This population lives in small isolated and scattered communities with low incomes where it is difficult to achieve 100% access to electricity by the grid extension. Therefore, it is necessary to create market mechanisms and promote off-grid electrification in which photovoltaic (PV) technology plays a fundamental role. This research assesses successful projects developed in Peru, Mexico, and Bolivia, where 3rd Generation Solar Home Systems (3G-SHSs) are being introduced to support off-grid initiatives. To do so, we applied a mixed-methods approach including a comparative case study analysis, an extensive literature review, focus group discussions, and field research. Thereby, the lessons learned reveal that confidence, commitment, and flexibility are the main pillars of rural electrification. Additionally, it is demonstrated that the combination of various business models—an energy service company, fee-for-service, pay-as-you-go, and a microfranchising—with 3G-SHSs is powerfully effective in terms of sustainability. Our findings are useful to policy makers, researchers, promoters, and other stakeholders to rethink intervention strategies in rural areas. Access to electricity must be a state policy to facilitate the participation of new actors, especially of the private sector and communities, and the introduction of innovative business models and high-quality technology.

Water impact of an optimal natural gas production and distribution system: An MILP model and the case-study of Mexico

This study presents a mathematical programming approach for evaluating the exploitation and distribution of shale gas from potential reserves at a national level, depending upon existing infrastructure and water availability. The study describes an MILP model that simultaneously integrates water management with the design and planning of the supply chain, from basins to distribution markets and fresh water supply from available watersheds. The model is applied to a case based on the potential exploitation of shale gas basins in Mexico. The parameters of the model are mostly taken from the databases of the country, processed through the geographic information system ArcGIS. The solution provides the optimal decisions for exploitation and distribution, as well as for freshwater source selection and optimal wastewater management. Water management strategies include disposal, wastewater treatment in municipal plants and onsite treatment. The negative impact of water consumption of the optimal exploitation systems is assessed based mainly on the estimation of the water stress index. Results show that the shale gas exploitation would favor the energy independence of the country, but the availability of freshwater for some municipalities would be compromised.

A Parametric Numerical Analysis of Factors Controlling Ground Ruptures Caused by Groundwater Pumping

AbstractA modeling analysis is used to investigate the relative susceptibility of various hydrogeologic configurations to aseismic rupture generation due to deformation of aquifer systems accompanying groundwater pumping. An advanced numerical model (GEPS3D) is used to simulate rupture generation and propagation for three typical processes: (i) reactivation of a preexisting fault, (ii) differential compaction due to variations in thickness of aquifer/aquitard layers constituting the aquifer system, and (iii) tensile fracturing above a bedrock ridge that forms the base of the aquifer system. A sensitivity analysis is developed to address the relative importance of various factors, including aquifer depletion, aquifer thickness, the possible uneven distribution and depth below land surface of the aquifer/aquitard layers susceptible to aquifer‐system compaction, and the height of bedrock ridges beneath the aquifer system which contributes to thinning of the aquifer system. The rupture evolution is classified in two occurrences. In one, the rupture develops at either the top of the aquifer or at land surface and does not propagate. In the other, the developed rupture propagates from the aquifer top toward the land surface and/or from the land surface downward. The aquifer depth is the most important factor controlling rupture evolution. Specifically, the probability of a significant rupture propagation is higher when the aquifer top is near land surface. The numerical results are processed by a statistical regression analysis to provide a general methodology for a preliminary evaluation of possible ruptures development in exploited aquifer systems susceptible to compaction and accompanying land subsidence. A comparison with a few representative case studies in Arizona, USA, China, and Mexico supports the study outcomes.

Forest Degradation Assessment Based on Trend Analysis of MODIS-Leaf Area Index: A Case Study in Mexico

: Assessing forest degradation has been a challenging task due to the generally slow-changing nature of the process, which demands long periods of observation and high frequency of records. This research contributes to efforts aimed at detecting forest degradation by analyzing the trend component of the time series of Leaf Area Index (LAI) collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) over Central Mexico from 2002 to 2017. The analysis of the trend component is proposed to overcome the challenge of identifying very subtle and gradual changes that can be undetected if only the raw time series is examined. Additionally, the use of LAI as an alternative to other widely used indexes (e.g., Normalize Difference Vegetation Index and Enhanced Vegetation Index) facilitates consideration of the structural changes evident from degradation though not necessarily observable with spectral indices. Overall, results indicate that 52% of the study area has experienced positive trends of vegetation change (i.e., increasing LAI), 37% has remained unchanged, and 11% exhibits some level of forest degradation. Particularly, the algorithm estimated that 0.6% (385 km2) is highly degraded, 5.3% (3406 km2) moderately degraded, and 5.1% (3245 km2) slightly degraded. Most of the moderate and highly degraded areas are distributed over the east side of the study area and evergreen broadleaf appears to be the most affected forest type. Model validation resulted an accuracy of 63%. Some actions to improve this accuracy are suggested, but also a different approach to validate this type of study is suggested as an area of opportunity for future research.

The Impact of Higher Education on Entrepreneurship and the Innovation Ecosystem: A Case Study in Mexico

Entrepreneurship is recognized as an engine for the economy. However, Latin America must promote higher opportunities for the creation of new businesses, especially for technology-based ventures. In this sense, the Center for Global Innovation and Entrepreneurship (CGIE) of the University of Texas at Austin offers a Master of Science in Technology Commercialization (MCCT) that prepares students with methodologies to promote the creation of new businesses in Mexico. This study aims to know the contribution of training to the creation of new companies, and its role in the innovation and the technology transfer processes, from the viewpoint of the participants. This research presents a case study that analyzes the impact of the MCCT through the analysis of the data of a survey answered by 109 former students of this center. Findings show that the methodologies developed by the MCCT allow the creation of technology-based enterprises and entrepreneurial skills in students. This study presents good practices that can be emulated by other countries in the region, as well as recognizing the great value the role of higher education in creating synergies between actors of the innovation ecosystem that strengthen social and economic growth.

Environmental-economic optimization for implementation of parabolic collectors in the industrial process heat generation: Case study of Mexico

Abstract This paper proposes an economic and environmental analysis for the design of solar heat systems and their incorporation in the industrial sector. A novel computational methodology is implemented to help the sustainable integration of parabolic trough collectors photothermal technology into the low and medium enthalpy industrial activities. A multivariate artificial neural network that involves environmental, operational, and economic aspects was used to transfer the phenomenon under study into a simple and fast computing multi-output mathematical model. The optimal trade-off between environmental benefits and investment viability of the hybrid solar plant’s design is obtained by a multi-objective optimization process. The objective functions consider the maximization in CO2 mitigation and net present value, and the minimization of the total life-cycle cost. The final optimal result is selected by using the TOPSIS decision-making method. Besides, a sensitivity analysis is conducted to report the system performance with respect to back-up boiler fuel type, climate region, the volume of the storage tank, and solar field area. The work contemplates the case study of a solar thermal plant based on parabolic collectors integrated into a pre-existing industrial process in Mexico. The study considered four of the most common climatic regions and the most representative heating fossil fuels in the national industrial sector. Based on the results, the best profitability and CO2 mitigation are achieved in warm climate regions. Moreover, diesel was identified as the most profitable back-up fuel scenario and natural gas as the least viable. Analysis of the energy contribution describes that implementation of parabolic trough collectors in the presented industrial process covers just over 40%–80% of the energy required, depending on the climate region. The presented methodology constitutes a rapid and low-cost computational tool which facilitates decision making for the implementation of solar heat industrial process systems. Moreover, it can be applied to other industrial processes with several photothermal technologies for clean heat generation.

Analysis of forest wood supply chains for round-wood production restricted by technical constraints

Aim of the study: Integrated information tools models are fundamental for analyzing supply chains as regards pattern of consumption and production. These models are very useful for availability estimations of natural resources when social and environmental uncertainties need to be addressed, as it is the case for forest wood supply chains. This work presents an analysis of a forest wood supply chain focusing on forest operations to estimate the availability of round-wood volume restricted by technical constraints using a local case study in Mexico. The theoretical and technical potentials of woody biomass availability were reviewed considering an assessment of forest operations for round-wood production.Area of the study: municipality of Santa Maria del Rio S.L.P. inside the forested land of San Antonio in Mexico.Material and methods: Geographical, historical and socioeconomic data and field work were used to develop technical constraints as extraction limits. Felling and extraction operations were analyzed resulting in a production rate of 2.48 m3 per productive machine hour.Main results: The theoretically produced standing timber accounted to 21,132 m3. After simulating technical constraints, the technically feasible supply of round-wood accounted to 2, 113 m3. Furthermore, a biomass flow chart for tracing biomass along the system boundaries was developed.Research highlights: With the given results, it is possible to give recommendations and conclusions for the improvement of wood supply chains supported by time studies values, technical constraints on terrain slope, harvesting intensity and mechanization level.Keywords: Mexico; modeling; forest operations; sustainable forest management.

Mixing processes between thermal waters and non-thermal waters: a case study in Mexico

The high content of toxic elements, such as As, in thermal water can cause water-quality problems when thermal water mixes with groundwater and/or surface water destined for human consumption. The objective of the study was to evaluate the mixing process between thermal and non-thermal waters in the Ixtapan de la Sal-Tonatico region of Mexico and to determine the resulting impacts on the quality of water for human consumption. The thermal springs of the study area had an average temperature of 35 °C and 5 g/L of total dissolved solids (TDS). The dominant ions were Cl− and Na+. The concentrations of As (1.7 mg/L), Fe (2.2 mg/L), and Mn (0.15 mg/L) and the water hardness (2087 mg CaCO3/L) exceeded the permissible limits for drinking water. Non-thermal springs, well water, and surface water were characterized as Ca–Na–Cl–HCO3, Ca–Mg–HCO3, and Na–Ca–Cl types, respectively, and had TDS values of 0.8, 0.2, and 0.4–3.9 g/L, respectively. The percentages of mixing were calculated based on the concentrations of conservative ions, such as Cl, B, Sr, and Li. The percentage of thermal water spring mixed with non-thermal spring water was around 11% and with surface water ranged from 10 to 30%. This variability is likely related to the proximity of surface water sources to the discharge points of thermal springs. As a result of mixing processes, the non-thermal water (non-thermal springs and surface waters) presents TDS, Cl−, Na+, hardness, As, Fe, and Mn values above those permitted by Mexican regulations for drinking water.

Full-waveform inversion for imaging and geologic interpretation: A deepwater Gulf of Mexico case study

Full-waveform inversion (FWI) is commonly used in model-building workflows to improve the resolution of the shallow velocity model and thus has a potentially positive impact on the imaging of deeper targets. This type of inversion commonly makes use of first arrivals from the longest offsets. However, signal from smaller offsets and later times can extend the depth range of the FWI-derived velocity model. Waveform inversion methods that use reflections have been shown to provide greater details and accuracy when deriving velocity models for deepwater exploration and production. The derived velocity sometimes provides an improved migrated image useful for interpretation in complex geology and enhances geologic features such as subsalt sediments, faults, and channels. We have used combination of FWI and a wavefield inversion approach known as reconstructed wavefield inversion (RWI) that makes use of diving waves and reflections to derive a velocity model for a deepwater survey off the coast of Veracruz in the Gulf of Mexico. The velocity model we derived from this approach produces an improved image of the target reservoir, and furthermore contains enough geologic details for direct interpretation. We enhanced the resolution of the velocity model further by performing a poststack amplitude inversion with the FWI + RWI derived velocity used as the input low-frequency model. The resulting high-resolution velocity provides an excellent product for detecting shallow gas anomalies, delineating a gas reservoir in an anticline structure as well as a system of deep, sand-filled channels. The inverted velocity also indicates a better correlation with sonic velocity measured from two blind wells than the initial tomography velocity, indicating the benefits of FWI approaches for quantitative reservoir characterization in deepwater environments.

An offshore Gulf of Mexico case study applying full-waveform inversion

Full-waveform inversion (FWI) is a high-resolution earth model-building technique based on recorded seismic data. Conventional FWI usually relies on diving and refracted waves to update the low-wavenumber/background components of the model; however, the update based on transmitted energy is often depth limited due to the limited offset range of the acquired data. To extend the FWI updating depth beyond the transmitted energy limits, we must use reflection data. Recently, industry interest has resumed in the potential for automated subsurface model-building, especially in complex geologic settings (e.g., salts), through data-driven minimization such as FWI. The business impact of such an automatic model-building technique would be significant in that it is proposed to improve the efficiency of any model-building exercise involving structural complexity and high uncertainty in seismic image interpretation. An ultimate expectation for the FWI technique is to build or update the salt geometry because these complex bodies have a first-order impact on image quality. We evaluate several examples using FWI for building a subsurface model, including salt boundary and salt velocity delineation, in geologically complex areas in the western Gulf of Mexico. The geology there comprises rugose and deformed shallow salt bodies with intracanopy high dip and close-proximity structures, resulting from regional basinward gliding and associated compressional mechanisms. Given the challenges for model building in such a complex setting, a data-fitting approach such as FWI with access to the full reflectivity record is proposed to provide practical solutions for an effective salt model update. Improving confidence in the seismic image and subsequent geologic understanding remains the core objective.

Warping least-squares inversion for 4D velocity change: Gulf of Mexico case study

We have developed a new trace-based, warping least-squares inversion method to quantify 4D velocity changes. There are two steps to solve for these velocity changes: (1) dynamic warping with phase constraints to align the baseline and monitor traces and (2) least-squares inversion for 4D velocity changes incorporating the time shifts and 4D amplitude differences (computed after trace alignment by warping). We have demonstrated this new inversion workflow using simple synthetic layered models. For the noise-free case, phase-constrained warping is superior to standard, amplitude-based warping by improving trace alignment, resulting in more accurate inverted velocity changes (less than 1% error). For synthetic data with 6% rms noise, inverted velocity changes are reasonably accurate (less than 10% error). Additional inversion tests with migrated finite-difference data shot over a realistic anticline model result in less than 10% error. The inverted velocity changes on a 4D field data set from the Gulf of Mexico are more interpretable and consistent with the dynamic reservoir model than those estimated from the conventional time-strain method.

Cogeneration Process Technical Viability for an Apartment Building: Case Study in Mexico

The objective of this paper is to evaluate and to simulate the cogeneration process applied to an apartment building in the Polanco area (Mexico). Considering the building’s electric, thermal demand and consumption data, the cogeneration process model was simulated using Thermoflow© software (Thermoflow Inc., Jacksonville, FL, USA), in order to cover 1.1 MW of electric demand and to supply the thermal needs of hot water, heating, air conditioning and heating pool. As a result of analyzing various schemes of cogeneration, the most efficient scheme consists of the use of a gas turbine (Siemens model SGT-100-1S), achieving a cycle with efficiency of 84.4% and a heat rate of 14,901 kJ/kWh. The economic results of this evaluation show that it is possible to implement the cogeneration in the building with a natural gas price below US$0.014/kWh. The use of financing schemes makes the economic results more attractive. Furthermore, the percentage of the turbine load effect on the turbine load net power, cogeneration efficiency, chimney flue gas temperature, CO2 emission, net heat ratio, turbine fuel flow and after burner fuel flow was also studied.

Comparative evaluation of rural electrification project plans: A case study in Mexico

Rural electrification project plans (REPP) aim to expand electricity access through adequate systems for communities without this service in developing countries. Many REPP have been developed, using different strategies in terms of energy uses covered, energy resources, electricity distribution and management models. This paper aims to analyze and compare REPP strategies. To do so, an evaluation methodology is developed, using a novel three-level assessment approach: the general definition at regional scale, the technical design at local scale, and the operation and maintenance (O&M) management. More specifically, ad hoc criteria are defined at each level to examine REPP fulfilment through quantitative and qualitative indicators. As case study, three plans from Chiapas (Mexico) are evaluated: national grid extension with national O&M; individual photovoltaic systems with regional O&M; and wind-photovoltaic microgrids with local O&M. Thus, the strengths and limitations of each REPP are identified in terms of strategies at regional scale, local scale and management model. Results show the ability of large plans to provide electricity to many families, while small plans may be adapted to the specific needs of end-users. The proposed criteria and indicators can be easily adjusted to evaluate REPP in different contexts to strengthen future plan strategies.

Feeding Patterns of Infants and Toddlers: The Mexico Case Study.

Understanding the feeding patterns of Mexican infants and toddlers has required large efforts due to the lack of recent reliable data. The double burden of obesity and micronutrient undernutrition is a public health problem in Mexico. This chapter reviews a series of papers reporting the FITS (Feeding Infants and Toddlers Study) Mexico effort. Secondary data analyses from a nationally representative sample of over 5,000 children from the Mexican National Nutrition and Health Study 2012 ENSANUT (Encuesta Nacional de Salud y Nutrición) were used to review the feeding and drinking patterns of Mexican infants and young children. Feeding patterns in Mexican children are established early in life. Low rates of exclusive breastfeeding were found in infants under 6 months of age. Only half of 6- to 47.9-month-old children consumed fruits, and 80% did not consume any vegetables (including potatoes) on the day of the survey. From the age of 12 months, more than 80% consumed sweets or sweetened beverages on any given day. For nutrients, 61% of infants 6-11.9 months old did not meet the estimated average requirement for iron, indicating a nutritional risk. High intakes of food groups with poor micronutrient and high energy levels might explain the nutritional condition for the Mexican population. Mexican experts have used this information to make recommendations and establish complementary feeding guidelines for healthy infants. Public policy and practice must now change accordingly.