“Mexico half way of making”: Carlos Chávez and the foundation of the National Institute of Fine Arts (INBA) (1945-1947)

Ana Garduño (2023, [Artículo, Artículo])

I am focusing on the interaction between a cultural agent, Carlos Chávez, and the government elite, related to the circumstances of the enunciation of a public and official organism, INBA (The National Institute of Fine Arts), because I assume that political relations are fundamental to understand a process that endorsed the official culture as an appendage of politics. In spite of its relevance, this subject has not been studied. Based on archival documentation (at the National Archive of Mexico and the archive of INBA) I am examining the cultural policies derived from the foundation of INBA. Due to the current pandemic situation, it was not possible to consult other documental sources. I am formulating that the concept of “high culture” was at the core of a wider conflict between governmental interests and those of representative social actors, and I conclude that this obstacle would have conferred a major political and symbolical importance to the Institute, and consequently, would restrict its budget.

Carlos Chávez INBA Agentes culturales Políticas institucionales Centralización artística HUMANIDADES Y CIENCIAS DE LA CONDUCTA HUMANIDADES Y CIENCIAS DE LA CONDUCTA Foundation of the National Institute of Fine Arts in Mexico (INBA), Cultural agents Institutional policies Artistic centralization

Commodity crops in biodiversity-rich production landscapes: Friends or foes? The example of cotton in the Mid Zambezi Valley, Zimbabwe

Frédéric Baudron Ken Giller (2022, [Artículo])

Land Sparing Land Sharing Human-Wildlife Conflicts CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BIODIVERSITY HOUSEHOLD SURVEYS LAND COVER LANDSCAPE MAMMALS CASH CROPS HUMAN-WILDLIFE RELATIONS LAND USE CHANGE

Diseño de un sistema eléctrico resiliente: Una evaluación multiobjetivo considerando dimensiones económicas, tecnológicas y políticas

EDMUNDO MOLINA PEREZ (2023, [Tesis de maestría])

https://orcid.org/0000-0003-0774-3205

Esta tesis aborda el desarrollo futuro del Sistema Eléctrico Nacional (SEN) de México en un contexto donde el país ha experimentado políticas energéticas contrastantes en una década. Frente a la alternancia de políticas energéticas opuestas bajo los gobiernos de Enrique Peña Nieto y Andrés Manuel López Obrador, se emplea la técnica de Robust Decision Making (RDM) para evaluar la resiliencia de sus políticas frente a un amplio rango de futuros plausibles. El estudio se centra en evaluar el desempeño del SEN bajo la implementación de cada política en términos de margen de reserva, costos de producción y emisiones directas de gases de efecto invernadero en un contexto de incertidumbre profunda. Los resultados revelan que las políticas energéticas más resilientes se caracterizan por una significativa incorporación de nuevas capacidades de generación, diversificación tecnológica y uso extensivo de energías limpias. Se observa que la política energética actual podría ser vulnerable por no alinearse con estos criterios. La investigación subraya la necesidad de un debate público y la formulación de políticas basadas en análisis objetivos y evidencia, enfocándose en el bienestar y progreso nacional.

Maestro en Prospectiva Estratégica

CIENCIAS SOCIALES CIENCIAS ECONÓMICAS ECONOMÍA SECTORIAL ENERGÍA

Agricultural value chains in Sudan: an annotated bibliography

Hugo De Groote Paswel Marenya (2023, [Libro])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL VALUE CHAINS CASH CROPS FOOD CROPS LIVESTOCK SOCIOECONOMIC ASPECTS GENDER SOCIAL INCLUSION POSTHARVEST LOSSES BIBLIOGRAPHIES

Corrección de defectos óseos en el área de Ingeniería tisular

Correction of bone defects by tissue Engineering

ROSA ALICIA SAUCEDO ACUÑA MONICA GALICIA GARCIA JUDITH VIRGINIA RIOS ARANA SIMON YOBANNY REYES LOPEZ (2012, [Artículo])

Hoy en día, los defectos óseos representan uno de los casos de mayor impacto en la salud debido a la frecuencia con que éstos ocurren a causa de traumatismos, fracturas, enfermedades congénitas o degenerativas. En la actualidad, los implantes de tejido óseo de gran volumen se encuentran severamente restringidos a causa de las limitaciones de difusión en la interacción con el ambiente del huésped para los nutrientes, intercambio gaseoso y eliminación de desechos. Es por ello que la corrección de los defectos óseos ha cobrado gran importancia en el área de Ingeniería tisular buscando mejorar las estrategias clínicas para su tratamiento. El propósito de esta revisión es proporcionar un panorama general del desarrollo de andamios para la regeneración de tejido óseo, mostrando los avances logrados en los ensayos in vitro e in vivo en la última década

Currently, bone defects cases represent a major impact on health due to how often they occur because of trauma, fractures, congenital or degenerative diseases. Now, bone implants to large volume are severely restricted because of the diffusion limitations in the interaction

with the environment of the host for nutrients, gas exchange and waste disposal. That is why the correction of bone defects has become very important in the field of tissue engineering looking to improve clinical strategies for treatment. The purpose of this review is to provide an overview of the development of scaffolds for bone tissue regeneration, showing the progress made in the in vitro and in vivo in recent decades.

MEDICINA Y CIENCIAS DE LA SALUD Ingeniería tisular regeneración ósea Andamio Tissue engineering Bone regeneration Scaffolds

Regional analysis of the wage discrimination in the indigenous workers in Mexico

Christian De la Luz-Tovar SIBYL ITALIA PINEDA SALAZAR (2023, [Artículo, Artículo])

The objective of this research is to estimate and decompose the wage gap between indigenous and non-indigenous workers by region in Mexico, to examine whether there are regional differences in the existing wage inequality that a priori affects the indigenous population and whether these differences can be attributed to the job profile of this group or by systematic labor discrimination against them. Using the data from the 2018 National Household Expenditure Revenue Survey (ENIGH-N) and the Oaxaca-Blinder decomposition, it was found that indigenous workers face a wage gap in all regions of the county. But, this gap is more pronounced in the center and south regions, where, on average, the associated component with labor discrimination has a percentage greater than 56. In contrast, in the north-central and northern regions of Mexico, the residual component is on average less than 33%, which suggests that the wage gap is explained by differences in productivity between groups.                         

Labor economics Ethnicity wage gap Indigenous population Regions Oaxaca-Blinder decomposition Economía laboral Brecha salarial étnica Población indígena Regiones Descomposición de Oaxaca-Blinder CIENCIAS SOCIALES CIENCIAS SOCIALES

Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding

Osval Antonio Montesinos-Lopez ABELARDO MONTESINOS LOPEZ RICARDO ACOSTA DIAZ Rajeev Varshney Jose Crossa ALISON BENTLEY (2022, [Artículo])

Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to

the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA Bayes Theorem Genome Inflammatory Bowel Diseases Models, Genetic Plant Breeding

Regional analysis of the wage discrimination in the indigenous workers in Mexico

Christian De la Luz-Tovar SIBYL ITALIA PINEDA SALAZAR (2023, [Artículo, Artículo])

The objective of this research is to estimate and decompose the wage gap between indigenous and non-indigenous workers by region in Mexico, to examine whether there are regional differences in the existing wage inequality that a priori affects the indigenous population and whether these differences can be attributed to the job profile of this group or by systematic labor discrimination against them. Using the data from the 2018 National Household Expenditure Revenue Survey (ENIGH-N) and the Oaxaca-Blinder decomposition, it was found that indigenous workers face a wage gap in all regions of the county. But, this gap is more pronounced in the center and south regions, where, on average, the associated component with labor discrimination has a percentage greater than 56. In contrast, in the north-central and northern regions of Mexico, the residual component is on average less than 33%, which suggests that the wage gap is explained by differences in productivity between groups.                         

Labor economics Ethnicity wage gap Indigenous population Regions Oaxaca-Blinder decomposition Economía laboral Brecha salarial étnica Población indígena Regiones Descomposición de Oaxaca-Blinder CIENCIAS SOCIALES CIENCIAS SOCIALES

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Nepal Seed And Fertilizer Project

Dyutiman Choudhary (2021, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SEED SEED INDUSTRY PRIVATE SECTOR MAIZE RICE INTEGRATED SOIL FERTILITY MANAGEMENT COVID-19