Uso potencial de pellets para el tratamiento de aguas contaminadas con arsénico en comunidades de Xichú, Gto., México

Pellets potential use for the treatment of contaminated water with arsenic in communities Xichú, Gto. Mexico

ALMA HORTENSIA SERAFIN MUÑOZ MELINA GUADALUPE MEDINA GARCIA FRANCISCO AGUSTIN VIDO GARCIA BERENICE NORIEGA LUNA ADRIAN ZAMORATEGUI MOLINA (2017, [Artículo])

En el presente trabajo se llevó a cabo el desarrollo del uso de pellets, provenientes de resi-duos lignocelulósicos, para el tratamiento de aguas contaminadas con arsénico de las comu-nidades del municipio de Xichú, Gto., México. Las muestras de agua, n = 72, se evaluaron con base en la NOM-127-SSA1-1994. La concentración más alta de arsénico fue arriba de los límites permisibles, 0.2 mg.L–1 ± 0.04 mg.L–1. Los pellets utilizados fueron a partir de aserrín, paja de trigo, agave y sorgo. Se optimizó la rampa de temperatura para la mejor consistencia de los pellets. Se realizaron varios diseños experimentales con los pellets, n = 162, a diferentes condiciones, para desarrollar el proceso de activación y tratamiento con Fe (III). Los pellets obtenidos fueron colocados en muestras de agua contaminadas con ar-sénico por 24 h. Se logró una remoción de arsénico a pH entre 6.5 a 7, del 98.50% ± 1.2%.

Present work was carried out development of use of pellets from lignocellulosic waste for arsenic-contaminated waters treatment in communities of the municipality of Xichu, Guanajuato, Mexico. Water samples, n = 72, were evaluated based on NOM-127-SSA1-1994.

The highest concentration of arsenic was above permissible limits, 0.2 mg.L–1 ± 0.04 mg.L–1. Pellets used were from sawdust, wheat straw, agave and sorghum. Temperature ramp to the best consistency of pellets is optimized. Several experimental designs with pellets were

performed,n = 162, in different conditions to develop activation process and treatment with Fe (III). Pellets obtained were placed in water samples contaminated with arsenic 24 h. Arsenic removal at pH between 6.5 to 7, of 98.50% ± 1.2% was achieved.

BIOLOGÍA Y QUÍMICA Arsénico Pellets Lignocelulósica Tecnologías sustentables Xichú, Gto. México Arsenic Lignocellulosic wastes Sustainable technologies

El impacto de la violencia en los flujos migratorios procedentes de Guatemala

Thania Berenice Hernández Alarcón (2021, [Tesis de maestría])

Con este trabajo buscamos entender cómo la violencia en el lugar de origen de una persona puede motivar su decisión de migrar. La aproximación teórica al fenómeno de la migración sugiere que la provisión relativa de bienes públicos es un factor en el análisis costo beneficio mediante el cual el agente evalúa la rentabilidad de la migración. Desde esta perspectiva, la búsqueda de beneficios pecuniarios, como un mayor salario, es compatible con la búsqueda de beneficios no pecuniarios, como mayores niveles de seguridad. Nos interesamos por evaluar lo anterior para el caso de Guatemala. Sirviéndonos de la variación trimestral de trecientos veintinueve municipios en una ventana de once años buscamos evidencia de que la tasa de migración de personas de origen guatemalteco que buscan empleo en México o Estados Unidos se correlaciona de manera positiva con la tasa de homicidios en sus municipios de origen. Nuestros resultados sugieren que esto se cumple y que aumentos en los niveles de violencia homicida pueden propiciar desplazamientos laborales.

Guatemala -- Emigration and immigration -- Effect of violence on -- Econometric models United States -- Emigration and immigration -- Econometric models. CIENCIAS SOCIALES CIENCIAS SOCIALES

Contracting in teams with network technologies

Giselle Labrador Badía (2020, [Tesis de maestría])

We develop a contracting model between the owner and the workers of a firm when production depends directly on a network of synergies among workers. We aim to answer how the owner of the firm uses the network structure to maximize profits. With this purpose, we analyze two contracting regimes: single wage and perfect discrimination. We find that individual network characteristics, as well as aggregate measures, affect profits and salaries. We also study the parameters for wich the incentives to discriminate and to account for the network structure are significant.

Externalities (Economics) -- Mathematical models. 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

Data for the synthesis, characterization, and use of xerogels as adsorbents for the removal of fluoride and bromide in aqueous phase

NAHUM ANDRES MEDELLIN CASTILLO ELIZABETH DIANE ISAACS PAEZ Liliana Giraldo Gutiérrez JUAN CARLOS MORENO-PIRAJAN ITZIA RODRIGUEZ MENDEZ SIMON YOBANNY REYES LOPEZ JAIME REYES HERNANDEZ SONIA JUDITH SEGOVIA SANDOVAL (2022, [Artículo])

"Groundwater with high fluoride concentrations has been recognized as one of the serious concerns worldwide. Besides, the fluoride released into the groundwater by slow dissolution of fluoride-containing rocks, various industries also contribute to fluoride pollution [1]. Excess intake of fluoride leads to various health problems such as dental and skeletal fluorosis, cancer, infertility, brain damage, thyroid diseases, etc. [2]. On the other hand, bromide is naturally present in surface and groundwater sources. However, during the chlorination process, bromide can be oxidized to HOBr, which can react with natural organic matter in water to form brominated organic disinfection byproducts, which are very harmful to human health [3]. Among various methods for water treatment, the adsorption process has been widely used and seems to be an efficient and attractive method for the removal of many contaminants in water, such as anions, in terms of cost, simplicity of design, and operation [4,5]. In the past years, xerogels and carbon xerogels, a new type of adsorbents, which are synthesized by the sol-gel polycondensation of resorcinol and formaldehyde, have gained attention due to their moldable texture and chemical properties [6]. Moreover, melamine addition in resorcinol and formaldehyde xerogels adds basic groups on its surface, favouring Lewis acid-base interactions between xerogels and other components by adsorption [7]. In this data article, the synthesis of three resorcinolformaldehyde (R/F) xerogels with an increasing amount of melamine (M) was carried out by colloidal polymerization (molar ratios of M/R = 0.5, M/R = 1.0, and M/R = 2.0). Additionally, samples of M/R = 0.5 xerogel were carbonized at 400, 450, and 550 degrees C under an inert atmosphere to increase their specific area. Organic and carbon xerogels obtained were characterized by FTIR, TGA, SEM, Physisorption of N 2, and the pH at the point of zero charge (pH PZC). All organic xerogels were also tested as adsorbents on the removal of fluoride and bromide ions from aqueous phase. The Freundlich, Langmuir, and Radke-Prausnitz isotherm models were applied to interpret the experimental data from adsorption equilibrium. Additionally, the data of the mass of the xerogel needed to remove fluoride and bromide from groundwater and fulfill the maximum concentration levels are also included."

Xerogels Melamine Colloidal polymerization Fluoride and bromide ions Adsorption BIOLOGÍA Y QUÍMICA QUÍMICA QUÍMICA

Optimizing nitrogen fertilizer and planting density levels for maize production under current climate conditions in Northwest Ethiopian midlands

Kindie Tesfaye Dereje Ademe Enyew Adgo (2023, [Artículo])

This study determined the most effective plating density (PD) and nitrogen (N) fertilizer rate for well-adapted BH540 medium-maturing maize cultivars for current climate condition in north west Ethiopia midlands. The Decision Support System for Agrotechnology Transfer (DSSAT)-Crop Environment Resource Synthesis (CERES)-Maize model has been utilized to determine the appropriate PD and N-fertilizer rate. An experimental study of PD (55,555, 62500, and 76,900 plants ha−1) and N (138, 207, and 276 kg N ha−1) levels was conducted for 3 years at 4 distinct sites. The DSSAT-CERES-Maize model was calibrated using climate data from 1987 to 2018, physicochemical soil profiling data (wilting point, field capacity, saturation, saturated hydraulic conductivity, root growth factor, bulk density, soil texture, organic carbon, total nitrogen; and soil pH), and agronomic management data from the experiment. After calibration, the DSSAT-CERES-Maize model was able to simulate the phenology and growth parameters of maize in the evaluation data set. The results from analysis of variance revealed that the maximum observed and simulated grain yield, biomass, and leaf area index were recorded from 276 kg N ha−1 and 76,900 plants ha−1 for the BH540 maize variety under the current climate condition. The application of 76,900 plants ha−1 combined with 276 kg N ha−1 significantly increased observed and simulated yield by 25% and 15%, respectively, compared with recommendation. Finally, future research on different N and PD levels in various agroecological zones with different varieties of mature maize types could be conducted for the current and future climate periods.

Maize Model Planting Density CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE MODELS SPACING NITROGEN FERTILIZERS YIELDS

Point placement of late vegetative stage nitrogen splits increase the productivity, N-use efficiency and profitability of tropical maize under decade long conservation agriculture

Hari Sankar Nayak C.M. Parihar Shankar Lal Jat ML JAT Ahmed Abdallah (2022, [Artículo])

Non-Linear Growth Model Nitrogen Remobilization Right Placement Precision Nitrogen Management CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GROWTH MODELS NITROGEN NUTRIENT MANAGEMENT

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

“Efecto marzo”: impacto de los nuevos médicos residentes en la salud de los pacientes

Jose Miguel Manrique Velasco (2021, [Tesis de maestría])

Al inicio de los ciclos educativos de los residentes, estos individuos proveen servicios de salud bajo una inadecuada supervisión como un proceso de aprendizaje en el que adquieren nuevas habilidades y conocimientos salud bajo la premisa de “aprender haciendo”, mas la falta inicial de estas expone a los pacientes a una baja calidad de atención que repercute en su salud lo cual no es ético. En consecuencia, la presente tesina evalúa los posibles efectos que tiene la masiva entrada de médicos residentes en México durante el mes marzo. Para lo cual emplea dos métodos con datos administrativos de las Secretaría de Salud. El primero es Diferencias en Diferencias, el cual tiene el objetivo de estimar el contrafactual de forma creíble suponiendo que las características de los individuos son invariantes en el tiempo y que en ausencia de la intervención el grupo de tratamiento seguirá la misma tendencia que el grupo de control. El segundo método es un event study cuyas virtudes son aportar evidencia de una buena identificación del método DID y descomponer el efecto en ventanas de tiempo para analizar como los cambios en el tiempo de la inexperiencia, el burnout, las fallas de coordinación y el learing-by-doing afectan al análisis. Bajo estos diseños se encuentra que hay efectos negativos en la salud de los pacientes a causa de la rotación de residentes los cuales pueden ser explicados por los altos niveles de estrés y cansancio documentados, la falta de práctica real en los procedimientos médicos, la baja supervisión de los residentes y el paradigma educativo de “aprender haciendo”. Además, se observa que estos efectos negativos solo ocurren en las primeras semanas después de la entrada de residentes para después desvanecer su efecto en los meses siguientes, lo cual indica que los residentes logran superar las limitaciones y sobrecarga del trabajo para finalmente otorgar un servicio de salud correspondiente a otros meses.

Patients -- Care -- Effect of residents (Medicine) on -- Mexico -- Econometric models. Public health -- Effect of residents (Medicine) on -- Mexico -- Econometric models. CIENCIAS SOCIALES CIENCIAS SOCIALES

La relación entre el crimen y ciclo económico en México: un enfoque espacial

Ricardo Masahiro Solis Ichien (2021, [Tesis de maestría])

En este trabajo se analiza la influencia del ciclo económico sobre los niveles de crimen en México desde el marco conceptual de la teoría de Cantor y Land (1985), los cuales distinguen el efecto de oportunidad y motivación criminal. Se presenta el análisis para el caso mexicano y se evalúa empíricamente el modelo de Cantor y Land para las 32 entidades federativas con datos trimestrales del 2010 a 2019. Utilizando un modelo econométrico que incorpora la interacción espacial en la tasa de crímenes y en el término de error, así como su rezago temporal, al que se le denomina como modelo espacial autorregresivo con errores autorregresivos de orden 1 (SARAR (1,1)) dinámico, se evalúa el modelo para siete tipos de crímenes: homicidios dolosos, secuestros, extorsiones, robo a negocios, robo a casa-habitación, robo de vehículo y robo a transeúnte. Los resultados muestran que se verifica la teoría de Cantor y Land (1985) para cuatro de los siete tipos de delitos. Los robos analizados se caracterizan como robos de necesidad y robos de especialización. Se encuentra evidencia del comportamiento espacial de la actividad criminal donde algunos delitos tienen un efecto regional y otros se concentran.

Crime -- Effect of business cycles on -- Mexico -- Econometric models. Violence -- Effect of business cycles on -- Mexico -- Econometric models. CIENCIAS SOCIALES CIENCIAS SOCIALES