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Women in Mexico are subject to unusually high and traumatic levels of violence. This paper reviews a workshop process done in Mexico City that addressed the problem of violence against women using the Anticipatory Experimentation methodology. Based on a workshop at Centro University in Mexico City on the eve of historic protests against violence against women, the paper provides an overview of contemporary challenges, historical changes, as well as deep mythological images and assumptions within Mexican society that are pathways to reconceptualization. Leveraging emerging issues and recovered narratives to address and reframe the problem, the paper concludes with the metaphor of the Chamana as the narrative seed from which new ideas and experiments might be developed to address violence against women in Mexico. [ABSTRACT FROM AUTHOR]

Objective: The Mexican government has pursued multiple initiatives to improve healthcare coverage and financial protection. Yet, out-of-pocket health spending and use of private sector providers in Mexico remains high. In this paper, we sought to describe the characteristics of public and private healthcare users, describe recent visit quality across provider types, and to assess whether perceiving the public healthcare sector as poor quality is associated with private health sector use. Methods and findings: We analyzed the cross-sectional People's Voice Survey conducted from December 2022 to January 2023. We used Chi-square tests to compare contextual, individual, and need-for-care factors and ratings of most recent visits between users of public (social security and other public providers) and private sector providers (stand-alone private providers and providers adjacent to pharmacies). We used a multivariable Poisson regression model to assess associations between low ratings of public healthcare sources and the use of private care. Among the 811 respondents with a healthcare visit in the past year, 31.2% used private sources. Private healthcare users were more educated and had higher incomes than public healthcare users. Quality of most recent visit was rated more highly in private providers (70.2% rating the visit as excellent or very good for stand-alone private providers and 54.3% for pharmacy-adjacent doctors) compared to social security (41.6%) and other public providers (46.6%). Those who perceived public health institutions as low quality had a higher probability of seeking private healthcare. Conclusion: Users rated public care visits poorly relative to private care; at the population level, perceptions of poor quality care may drive private care use and hence out-of-pocket costs. Improving public healthcare quality is necessary to ensure universal health coverage. [ABSTRACT FROM AUTHOR]

Ocean energy sources are a promising source of energy. However, simulating a hydrokinetic farm with multiple units requires significant computational resources, while physical experimentation on site is expensive. Therefore, the scientific challenge is to develop analytical and experimental tools that consider real aspects of areas with generation potential in a controlled laboratory environment. This paper presents a theoretical and experimental tool for analysing the interconnection of a hydrokinetic energy farm comprising 20 generation units. The test bench is a Power Hardware in the Loop type, consisting of one physical prototype generator to scale and 19 discrete averaged models operating in real-time. The system allows generators to interact through an amplifier, emulating the impact of power injection in a small electrical network. This is based on the variability of the marine resource, specifically the current velocities in the Cozumel-Mexico channel. Unlike other publications, the most significant contribution of this work is a complete feasible emulation of a marine current plant interconnected to an electrical grid, where the objective is to have a global analysis of the operation of each generation unit and the impact of the interconnection as a whole, considering that such information is of utmost importance for the execution of future projects of power generation from the sea. [ABSTRACT FROM AUTHOR]

The detection of seismic activity precursors as part of an alarm system will provide opportunities for minimization of the social and economic impact caused by earthquakes. It has long been envisaged, and a growing body of empirical evidence suggests that the Earth's electromagnetic field could contain precursors to seismic events. The ability to capture and monitor electromagnetic field activity has increased in the past years as more sensors and methodologies emerge. Missions such as Swarm have enabled researchers to access near-continuous observations of electromagnetic activity at second intervals, allowing for more detailed studies on weather and earthquakes. In this paper, we present an approach designed to detect anomalies in electromagnetic field data from Swarm satellites. This works towards developing a continuous and effective monitoring system of seismic activities based on SWARM measurements. We develop an enhanced form of a probabilistic model based on the Martingale theories that allow for testing the null hypothesis to indicate abnormal changes in electromagnetic field activity. We evaluate this enhanced approach in two experiments. Firstly, we perform a quantitative comparison on well-understood and popular benchmark datasets alongside the conventional approach. We find that the enhanced version produces more accurate anomaly detection overall. Secondly, we use three case studies of seismic activity (namely, earthquakes in Mexico, Greece, and Croatia) to assess our approach and the results show that our method can detect anomalous phenomena in the electromagnetic data. [ABSTRACT FROM AUTHOR]

The growing expansion of the manufacturing sector, particularly in Mexico, has revealed a spectrum of nearshoring opportunities yet is paralleled by a discernible void in educational tools for various stakeholders, such as engineers, students, and decision-makers. This paper introduces a state-of-the-art framework, incorporating virtual reality (VR) and artificial intelligence (AI) to metamorphose the pedagogy of advanced manufacturing systems. Through a case study focused on the design, production, and evaluation of a robotic platform, the framework endeavors to offer an exhaustive educational experience via an interactive VR environment, encapsulating (1) Robotic platform system design and modeling, enabling users to immerse themselves in the design and simulation of robotic platforms under varied conditions; (2) Virtual manufacturing company, presenting a detailed virtual manufacturing setup to enhance users' comprehension of manufacturing processes and systems, and problem-solving in realistic settings; and (3) Product evaluation, wherein users employ VR to meticulously assess the robotic platform, ensuring optimal functionality and customer satisfaction. This innovative framework melds theoretical acumen with practical application in advanced manufacturing, preparing entities to navigate Mexico's manufacturing sector's vibrant and competitive nearshoring landscape. It creates an immersive environment for understanding modern manufacturing challenges, fostering Mexico's manufacturing sector growth, and maximizing nearshoring opportunities for stakeholders. [ABSTRACT FROM AUTHOR]

Mathematical algorithms relate satellite data of ocean color with the surface Chlorophyll-a concentration (Chl-a), a proxy of phytoplankton biomass. These mathematical tools work best when they are adapted to the unique bio-optical properties of a particular oceanic province. Ocean color algorithms should also consider that there are significant differences between datasets derived from different sensors. Common solutions are to provide different parameters for each sensor or use merged satellite data. In this paper, we use satellite data from the Copernicus merged product suite and in situ data from the southernmost part of the California Current System to test two widely used global algorithms, OCx and CI, and a regional algorithm, CalCOFI2. The OCx algorithm yielded the most favorable results. Consequently, we regionalized it and conducted further testing, leading to significant improvements, especially in eutrophic and oligotrophic waters. The database was then separated according to (a) dynamic boundaries in the area, (b) bio-optical properties, and (c) climatic conditions (El Niño/La Niña). Regional algorithms were obtained and tested for each partition. The Chl-a retrievals for each model were tested and compared. The best fit for the data was for the regional algorithms that considered the climatic conditions (El Niño/La Niña). These results will allow for the construction of consistent regionally adapted time series and, therefore, will demonstrate the importance of El Niño/La Niña events on the bio-optical properties of the area. [ABSTRACT FROM AUTHOR]

The transport sector is under scrutiny because of its significant greenhouse gas emissions. Essential strategies, particularly the adoption of zero- and low-emission vehicles powered by electricity, are crucial for mitigating emissions in road transport. Pickups, which are integral to Mexico's fleet, contribute to such emissions. Thus, implementing effective policies targeting pickups is vital for reducing air pollution and aligning with Mexico's decarbonization objectives. This paper presents a simulation model based on system dynamics to represent the adoption process of zero- and low-emission vehicles, with a focus on pickups and utilizing data from the Mexican case. Three policy evaluation scenarios are proposed based on the simulation model: business as usual; disincentives for zero- and low-emission vehicles; and incentives for unconventional vehicles. One of the most significant findings from this study is that even in a scenario with a greater number of vehicles in circulation, if the technology is fully electric, the environmental impact in terms of emissions is lower. Additionally, a comprehensive sensitivity analysis spanning a wide spectrum is undertaken through an extensive computational process, yielding multiple policy scenarios. The analysis indicates that to achieve a maximal reduction in the country's emissions, promoting solely hybrid electric vehicles and plug-in hybrid electric vehicles is advisable, whereas internal combustion engines, vehicular natural gas, and battery electric vehicles should be discouraged. [ABSTRACT FROM AUTHOR]

Rocky Mountain spotted fever (RMSF) is an international and quintessential One Health problem. This paper synthesizes recent knowledge in One Health, binational RMSF concerns, and veterinary and human medical perspectives to this fatal, reemerging problem. RMSF, a life-threatening tick-borne disease caused by the bacterium Rickettsia rickettsii, emerged during the first decade of the 21st century in impoverished communities in the southwestern US and northern Mexico. Lack of an index of suspicion, delay in diagnosis, and delayed initiation of antibiotic treatment contribute to fatality. Campaigns targeting dog neutering, restraint to residents' properties, and on-dog and on-premises treatment with acaricides temporarily reduce prevalence but are often untenable economically. Contemporary Mexican RMSF is hyperendemic in small communities and cities, whereas epidemics occur in the western US primarily in small tribal communities. In in both locations, the epidemics are fueled by free-roaming dogs and massive brown dog tick populations. In the US, RMSF has a case fatality rate of 5% to 7%; among thousands of annual cases in Mexico, case fatality often exceeds 30%.1,2 Numerous case patients in US border states have recent travel histories to northern Mexico. Veterinarians and physicians should alert the public to RMSF risk, methods of prevention, and the importance of urgent treatment with doxycycline if symptomatic. One Health professionals contribute ideas to manage ticks and rickettsial disease and provide broad education for the public and medical professionals. Novel management approaches include vaccine development and deployment, acaricide resistance monitoring, and modeling to guide targeted dog population management and other interventions. [ABSTRACT FROM AUTHOR]

This paper aims to simulate total factor productivity, following the original proposal made by Cobb and Douglas (1928). Estimates with annual frequency are computed for the United States during two periods, i.e. 1899-1992 and 1933-2019. In the case of Mexico, estimates are computed for the 1993-2015 period. An income distribution in favor of capital in recent decades is found both for the United States and México. Capital share has grown in the United States from 25% in 1899-1922 to 89% in 1993-2019, while for Mexico it has been 82% for 1993-2015. Functional income distribution requires close monitoring. [ABSTRACT FROM AUTHOR]

The demand for different energy goods and services is a fundamental component in a country's economic structure for development. Understanding it is vital in designing economic policies, such as taxes, that can improve the welfare of the population. A comprehension of the distributional effects of elasticities and the application of them to simulate household responses to price changes, as well as a calculation of the welfare impacts on poor and rich households in Mexico, should inform policy design. This paper uses the Household Income and Expenditure Survey (ENIGH) from 1996 to 2018 to estimate the demand of Mexican households for fuels, specifically electricity, liquefied petroleum gas, and gasoline. A Quasi Ideal Quadratic Demand System (QUAIDS) is employed to analyse the effects of removing energy subsidies and introducing a carbon tax. The results indicate that welfare losses would be regressive concerning electricity price increases, while changes in gasoline prices would be progressive. Redistributing the tax revenues accrued by removing energy subsidies and imposing the carbon tax would have more progressive effects on the economy of Mexican households, with welfare gains of up to 350% for the poorest households in the case of electricity consumption taxes. [ABSTRACT FROM AUTHOR]

Background. Perinatal depression (PND) is a clinical disease developed in any stage during the pregnancy and postpartum period with serious health and economic implications. Objective. The aim of this work was to analyze via bibliometrics indicators Mexico's production on PND to provide a view of the academic landscape and a comprehensive reference for subsequent research in the country. Method. The Scopus and Web of Science (WoS) databases were used to perform a search for peer reviewed papers related to PND in México. The search was made following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The extracted data were processed with VOS Viewer to examine link strength and clusters associations of diverse bibliometrics variables. Results. A total of 132 records were retrieved and we included 70 studies in the bibliometric analysis after application of the exclusion criteria. The authors with more papers were Navarrete L., and Asunción Lara M. The institutions with more papers were the National Institute of Perinatology, Ramón de la Fuente National Institute of Psychiatry, and National Institute of Public Health of Mexico. A diminution of the research considered in PND is observed in the last two years. Four keyword clusters were identified related to PND: symptoms, prevalence, pregnancy. Discussion and conclusion. The scarce literature concerning PND in Mexico compared with other countries could be due the limited collaboration between the health institutes. An urgent need to increase research on PND in Mexico is evident to be applicable in the management of resources in the healthcare system. [ABSTRACT FROM AUTHOR]

In Mexico, there is a lack in academic research about bisexual Health-Disease-Attention process. This paper analyzes the main problems about health-disease for bisexual people with a Social Medicine and a Collective Health approach. In order to do this analysis, this paper offers a systematization of research's discoveries related to the Health-Disease-Attention process in bisexual people. Problems on health-disease for bisexual people include worse mental health conditions in comparison to gay and lesbian people. As psychologists have few contextualized knowledge about bisexual health-disease situations, then they cannot adequately respond to bisexual people needs. Bisexual Health-Disease-Attention process is an historical and social product where the lack of visibility and the negative valuation functions as mechanisms to regulate people's sexuality, which can be reproduced in Health-Attention places, such as Mental Health ones. [ABSTRACT FROM AUTHOR]

This paper aims to introduce a novel family of probability distributions by the well-known method of the T–X family of distributions. The proposed family is called a "Novel Generalized Exponent Power X Family" of distributions. A three-parameters special sub-model of the proposed method is derived and named a "Novel Generalized Exponent Power Weibull" distribution (NGEP-Wei for short). For the proposed family, some statistical properties are derived including the hazard rate function, moments, moment generating function, order statistics, residual life, and reverse residual life. The well-known method of estimation, the maximum likelihood estimation method is used for estimating the model parameters. Besides, a comprehensive Monte Carlo simulation study is conducted to assess the efficacy of this estimation method. Finally, the model selection criterion such as Akaike information criterion (AINC), the correct information criterion (CINC), the Bayesian information criterion (BINC), the Hannan–Quinn information criterion (HQINC), the Cramer–von-Misses (CRMI), and the ANDA (Anderson–Darling) are used for comparison purpose. The comparison of the NGEP-Wei with other rival distributions is made by Two COVID-19 data sets. In terms of performance, we show that the proposed method outperforms the other competing methods included in this study. [ABSTRACT FROM AUTHOR]

With the implementation of the North American Free Trade Agreement (NAFTA), Mexico experienced a rapid expansion in highly industrialized food and beverage products. This has transformed supply and distribution structures and led to changes in dietary patterns. The objective of this paper is to explain how these transformations led to the configuration of a hybrid distribution and consumption scheme that affected the expenditure, frequency and quantities of ultra-processed and fast foods consumed in Mexican households during the period 2000-2020. This hybrid model is associated with an increase in diseases such as obesity and chronic degenerative diseases. [ABSTRACT FROM AUTHOR]

The presence of the conservatives in Mexico, and their main characters, is long-standing. In Mexican history, some of the conservative movements have been present in religious thinking, especially in Catholicism, e.g., the quick departure from socio-cultural and political Mexican spaces as a consequence of the evangelical Spanish process, whose roots come from the XVI century Of the population in contemporary Mexico (7.7% belong to Catholicism, 2.5% to Evangelical Christians and Protestants, and 2.5% to non-Christian groups, while 8.1% do not follow a religion. Catholicism has a significant presence and influence on different forms of belief and practice in daily life in Mexico. This paper aims to highlight the role of the conservative movement called Frente Nacional por la Familia. It presents its history as the heritage of other conservative movements in Mexico, the stages of its formation, and the agenda and intervention in public life. The methodological approach is qualitative, using multi-situated ethnography. The results allow us to visualize the construction of the public agenda with legislative strategies that have operated with relative success and national presence, obstructing the progress of the proposals of feminist groups and sexual diversity and the defense of a national and cultural project that has as one of the symbols the traditional family. [ABSTRACT FROM AUTHOR]

The present study was a meta-analysis compiling research on digital citizenship conducted in Mexico in 2011 - 2023. It was guided by the objective of arguing, analyzing and categorizing the lines of knowledge generation and application (LGAC) related to digital citizenship in Mexico. The methodology applied was meta-analysis where 88 research studies were documented: 47 papers, 33 journal articles and 8 theses. The studies found support the existence of six LGAC in Mexico. It was concluded that the studies are related to understanding the way in which society appropriates digital technologies, interactions through social networks and the manifestations of digital identity. Another point to highlight is that the study of digital citizenship has been used to analyze the acquisition of digital skills and attitudes, social issues addressed by digitalization, the roles played by educational actors in the virtual environment and the promotion of multiculturalism. The studies found provide relevance to the LGAC, and allow concluding that digital citizenship is a topic present in research on educational technology in Mexico. [ABSTRACT FROM AUTHOR]

Ecoepidemiology is an emerging field that attempts to explain how biotic, environmental, and even social factors influence the dynamics of infectious diseases. Particularly in vector-borne diseases, the study under this approach offers us an overview of the pathogens, vectors, and hosts that coexist in a given region and their ecological determinants. As a result of this, risk predictions can be established in a changing environment and how it may impact human populations. This paper is aimed at evaluating some ecoepidemiological characteristics of Chagas disease in a natural reserve in southeastern Mexico that borders human settlements. We carry out a cross-sectional study in 2022 where we search insects manually and with light traps. We set traps for small mammals and bats and conducted interviews with the inhabitants living around the study site. We identified the presence of Triatoma dimidiata and T. huehuetenanguensis species with a percentage of TcI T. cruzi infection of 68.4% (95% CI: 66.9-69.9). Temperature and humidity were not determining factors for the probability of insect capture. Of the 108 wild mammals (Chiroptera, Rodentia, and Didelphimorphia), none was infected with T. cruzi. Knowledge about Chagas disease in nearby inhabitants is poor, and some characteristics were found on the periphery of dwellings that could offer a refuge for insect vectors. With this information, surveillance strategies can be generated in the study area that reduce the risk of transmission of T. cruzi parasite to humans, and it is expected to motivate the use of this field in future research. [ABSTRACT FROM AUTHOR]

This paper presents a detailed analysis of a previous work that described the dynamic behavior of an antique stamp mill. The stamp mill application was for breaking ore stones as part of silver production. The dynamic analysis was established from a modern description of the kinematic chain. Since there is no technical data or archeological reports, the model was reconstructed using the dimensions described in original documents and assuming the operation conditions from different technical references. The model was validated using the typical production rates from the pre-industrial revolution period (XVI to XVIII centuries). The results show a proper method for reconstructing the engineering data of antique mechanisms and provide the basis for reproducing these types of mechanisms with modern engineering concepts. The data can be extrapolated to other similar mills that were developed based on this functional principle. [ABSTRACT FROM AUTHOR]

Central Americans living in Mexico remain a small group (100 thousand) relative to the size of the Mexican population. However, they experienced accelerated growth between 2000 and 2020, with Guatemalans as the largest group and Hondurans as the most dynamic one. The previous literature has found a positive and significant, albeit decreasing, income advantage of Central American workers in Mexico. Meanwhile, the percentage of migrant women reported as spouses has gone down and the female labor force has increased. The paper uses information from the 2000, 2010, and 2020 Mexican censuses as well as the 2015 Intercensal Survey to compare access to the labor market for men and women from Guatemala, El Salvador, and Honduras residing in Mexico. We compare marital status, female labor force participation, main economic sectors, human capital, and income levels of the men and women of each of the three nationalities considered, seeking to identify from a gender perspective the differentiated labor performance of each nationality. [ABSTRACT FROM AUTHOR]

Cyberaggression is an important problem today; it can affect adolescents in different ways. Therefore, reliable and valid measures are necessary to better study the phenomenon. The aim of the present study was to generate validity and reliability evidence for a Spanish-language cyberaggression scale from Garaigordobil, (2017) in a population of 1695 adolescents from northwestern Mexico (51.5% female) between 12- and 15-years-of-age. The results of this study contribute to the research and focus on cyberaggression in adolescents in Mexico. The measure used in this paper detects the different roles, including the bystander, rigorously testing the reliability and validity of the measure, providing a solid tool to evaluate cyberaggression in the Mexican context and guide evidence-based interventions and policies in educational settings. [ABSTRACT FROM AUTHOR]

This paper examines the impact of social pensions on old‐age poverty. To achieve causal identification, we leverage the reduction in the minimum eligibility age of Mexico's flagship non‐means‐tested social pension program. We find that the program's expansion significantly reduced extreme poverty, mainly among indigenous seniors and in rural areas. However, it had negligible effects on labor force participation, suggesting that social pensions were not effective in ensuring minimum economic well‐being and simultaneously inducing retirement among seniors at early stages of old age. The program's small cash transfer and mistargeting are among the main explanations. [ABSTRACT FROM AUTHOR]

The aim of this paper is to examine the effect of economic openness on wage dispersion. To this end, using a fixed effects panel model, we evaluate the impact of exports and foreign direct investment (FDI), as well as productivity and education, on wage dispersion in 14 economic subsectors in Mexico during the period 1999-2021. The main findings show that: i) increasing exports tend to diminish wage dispersion; ii) the flow of FDI seems to increase wage dispersion; iii) productivity and the heterogeneity of the productive network are determining factors in the dynamics of average wages. In this context, it is important to implement a variety of industrial and labour policies to effectively absorb the dynamic advantages associated with economic openness, such as the reduction of wage dispersion. [ABSTRACT FROM AUTHOR]

This paper demonstrates, using a panel data model, that mainly firm-specific (microeconomic) versus macroeconomic variables affect the long-run profitability of a group of banks in Mexico in the pre- and COVID-19 periods. Interbank deposit, deposit rate, bank size, size of non-performing loan portfolio, delinquency, operating expenses, traditional deposit, salary, unemployment, and interest rate have statistical influence on bank profitability, but this relationship changes in the COVID-19 period. These results can be useful in the decisions of the different areas of banks, as well as for the design of public policies aimed at maintaining the stability of the banking system. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to the strategic planning of the supply chain for lime cultivation. The uncertainty associated with lime production due to factors such as transportation, crime, and water availability, among others, represents different challenges. To address these challenges, the authors propose the use of machine learning tools coupled with deterministic optimization to obtain optimal solutions for the supply chain for future years. This paper highlights the use of justice schemes to ensure an equitable distribution of lime production between farmers and learning machines to quantify the insecurity impact on lime production in Michoacan. The problem can be solved using a Mixed-Integer Linear Programming (MILP) model that focuses on maximizing economic benefits, minimizing the use of irrigation water in crops, and minimizing Carbon Dioxide Equivalent (CO 2eq) emissions within the supply chain. The results demonstrate that the proposed approach can effectively address the challenges facing the lime production supply chain, resulting in an optimized and equitable lime production and distribution between farmers using the Social Welfare Justice scheme. Scenario A presents a utopian viewpoint with maximum benefits and minimum CO 2eq generated emissions, corresponding to $ 4.08 × 109 and 1.94 × 106 tons of CO 2eq , respectively. This paper contributes to the growing body of literature on the use of Artificial Intelligence (AI) in supply chain management, specifically in the optimization of supply chain processes. [Display omitted] [ABSTRACT FROM AUTHOR]

The paper uses fifty-three social tables, ranging from Greece in 330 BCE to Mexico in 1940 to estimate the share and level of income of the top 1 % in pre-industrial societies. The share of the top 1 % covers a vast range from around 10 % to more than 40 % of society's income and does not always move together with the estimated Gini coefficient and the Inequality Extraction Ratio. I provide a taxonomy of pre-industrial societies based on the social class and type of assets (land, control of government, merchant capital, citizenship) that are associated with the top classes as well as lack of assets associated with poverty. [ABSTRACT FROM AUTHOR]

In the early stages of health attention, such as in the examination rooms, patients are generally treated using a First In First Treat (FIFT) logic. This treatment style is inefficient from an operational view as it leads to long waiting times for critical patients. Based on optimization and discrete-event simulation, this paper introduces a hybrid model to assign patients priorities and exam rooms. Patients arrive to the system following a probability function, and for every discrete interval, a mixed-integer linear optimization model is used to allocate patients, considering health priority, preparation times, and availability of time and resources. Instances of the problem are defined using information from a health system in Mexico. Additional to the linear model, a heuristic algorithm is proposed, composed of two phases and aims to provide good, feasible, and fast solutions without ensuring optimality. Computational experiments showed that the linear model is more appropriate for small instances since the heuristic is faster and the relative deviations with respect to the linear model are below five percent. Finally, the discrete-event simulation is run for two cases: (1) with a FIFT logic and (2) using the optimization model. The hybrid model reduces the global waiting times up to 90% and the number of high health priority patients who are not treated up to 100%. • A mixed-integer linear model and a heuristic algorithm are used to allocate patients. • Optimization-simulation model reduced waiting times in primary health centers. • Optimization-simulation model reduced the number of non-treated patients. • The hybrid model is applied in a real Mexico's health system. [ABSTRACT FROM AUTHOR]

This article analyzes energy poverty in Latin America and the Caribbean and the importance of energy efficiency to address this issue. The paper also touches upon energy subsidies in Mexico and their negative environmental and social consequences. Then, the article studies the potentially detrimental billing practices of Mexico's state electricity company, which are provoked by the enterprise's growing past-due portfolio and losses, and the possible infringement of electricity consumers' rights. The authors propose three courses of action for consumers to protest the company's possibly perjudicial billing. Finally, the authors suggest that a distributed electricity system in Mexico could combat energy poverty and strengthen electricity users' rights. [ABSTRACT FROM AUTHOR]

This paper examines the effects of foreign exchange (FX) communications on FX markets in Colombia and Mexico. Our estimations follow the calendar-time portfolio approach using daily data between 2000 and 2019 on exchange rates and known risk factors. We find an asymmetric effect of such communications: while there is strong evidence indicating that communications aimed at weakening the local currency affect the exchange rate level in the intended direction, there is no evidence of impact when examining communications intended to strengthen it. These results are consistent with fear of appreciation and with previous evidence from developed economies. • Monetary authorities use foreign exchange communications (FXC) to influence the exchange rate. • FXC in Colombia and Mexico are evaluated during the 2001-2019 period. • The calendar-time portfolio approach is used to evaluate FXC in both countries. • FXC aimed at weakening the domestic currency affect the exchange rate, while those intended to strength it have no impact. • Results are consistent with fear of appreciation and previous evidence from advanced economies. [ABSTRACT FROM AUTHOR]

This paper presents evidence of large learning losses and partial recovery in Guanajuato, Mexico, during and after the school closures related to the COVID-19 pandemic. Learning losses were estimated using administrative data from enrollment records and by comparing the results of a census-based standardized test administered to approximately 20,000 5th and 6th graders in: (a) March 2020 (a few weeks before school closed); (b) November 2021 (2 months after schools reopened); and (c) June of 2023 (21 months after schools re-opened and over three years after the pandemic started). On average, students performed 0.2 to 0.3 standard deviations lower in Spanish and math after schools reopened, equivalent to 0.66 to 0.87 years of schooling in Spanish and 0.87 to 1.05 years of schooling in math. By June of 2023, students were able to make up for ∼ 60% of the learning loss that built up during school closures but still scored 0.08–0.11 standard deviations below their pre-pandemic levels (equivalent to 0.23–0.36 years of schooling). [ABSTRACT FROM AUTHOR]

Around the world, an increasing amount of bridge infrastructure is ageing. The resources involved in the reassessment of existing assets often exceed available resources and many bridges lack a minimum structural assessment. Therefore, there is a need for comprehensive and quantitative approaches to assess all the assets in the bridge network to reduce the risk of collapsing, damage to infrastructure, and economic losses. This paper proposes a methodology to quantify the structural criticality of bridges at a network level. To accomplish this, long-run site-specific simulations are conducted using Bayesian Networks and bivariate copulas, utilizing recorded traffic data obtained from permanent counting stations. To enhance the dataset, information from Weigh-in-Motion systems from different regions was integrated through a matching process. Subsequently, the structural response resulting from the simulated traffic is assessed, and the extreme values of the traffic load effects are obtained for selected return periods. Site-specific bridge criticality as a performance indicator for traffic load effects is derived by comparing the extreme load effects with the design load effects. The outcomes are mapped to facilitate visualization employing an open-source geographic information system application. To illustrate the application of the methodology, a total of 576 bridges within a national highway network are investigated, and a comparison with a popular simplified method is shown. The methodology herein presented can be used to assist in assessing the condition of a bridge network and prioritizing maintenance and repair activities by identifying potential bridges subjected to major load stress. • Methodology for mapping extreme load effects due to heavy vehicles in bridge networks • Evaluation of bridge criticality as a performance indicator for traffic load effects • Simple yet robust method using Bayesian Networks and copulas for traffic simulation • Application of the methodology to Mexico's national bridge network as case study [ABSTRACT FROM AUTHOR]

In this paper, we examine the impact of stress in the global supply chains on inflation and monetary policy in Mexico, a representative emerging market economy. Using non-linear local projections, we estimate the degree of monetary policy tightening required in a high-stress supply chain environment and compare it to that in a low-stress environment. We instrument the monetary policy shocks with shocks to the federal funds rate. Results suggest that in a high-stress regime, the effect of an increase in the monetary policy interest rate on inflation over a one-year period is reduced considerably. We argue that this reduction is due to the slow response of inflation expectations to a monetary policy tightening in a high-stress regime. Furthermore, raising the interest rate has an effect on producer price inflation, a channel that is absent in a low-stress regime. This finding highlights the role of monetary policy in stabilizing inflation when facing supply shocks that are not necessarily permanent. • Stress in the global supply chain has a non-linear effect on inflation. • Monetary policy channels are affected in a representative emerging market economy. • Evidence from Mexico shows monetary policy tightening should be considerably larger. • Monetary policy should react to temporary supply shocks. • Non-linear local projections are used; shock identification via instruments. [ABSTRACT FROM AUTHOR]

E-commerce's rapid growth, combined with customer demand for fast shipping, has significantly escalated last-mile transportation, particularly home deliveries. This surge calls for novel strategies to optimize vehicle utilization while maintaining timely delivery. In response, many online retailers are incentivizing customers to embrace delayed home deliveries by offering economic incentives. Nonetheless, current transportation systems fall short in accommodating orders with extended delivery windows, primarily adhering to the First-In-First-Out rule and distance minimization via the Vehicle Routing Problem (VRP). In this paper, we introduce a new consolidation-based delivery methodology that addresses these challenges. Our approach accounts for orders with daily-based time windows and also anticipates future demand realizations (i.e., expected incoming orders). We characterize this consolidation problem using a Mixed Integer Linear Programming model and propose a custom metaheuristic approach that can tackle the problem on a large-scale setting, introducing a significant novelty approach in last-mile delivery research. We applied our methodology to one of Mexico's largest retailers and compared its performance against the company's existing transportation systems. Our approach substantially improves vehicle utilization and yields considerable reductions in distance traveled, time, and overall transportation costs, achieving cost savings of up to 52%. These savings represent tangible benefits, enabling potential revenue enhancements for businesses and cost-effective, timely deliveries for consumers. Additionally, the increased vehicle utilization implies fewer vehicles are needed for the same volume of deliveries, thereby enhancing operational efficiency. This innovative approach, therefore, presents a practical and highly effective solution for managing large-scale last-mile delivery scenarios. [ABSTRACT FROM AUTHOR]