Estabilidad de catalizadores Ni soportados en ZrO₂ durante la hidrogenación selectiva de CO₂ hacia metano

En el presente trabajo se estudió el efecto del método de síntesis de soportes de ZrO₂, y el efecto de la carga metálica sobre la hidrogenación catalítica del CO₂ para la producción de metano. Los soportes utilizados fueron ZrO₂ comercial (ZrO₂-COM), y óxidos de zirconio sintetizados por los métodos de coprecipitación (ZrO₂-COP) y Sol-Gel (ZrO₂-SG). Para los catalizadores sintetizados se utilizaron cargas metálicas de níquel del 10 y 20% peso. La evaluación catalítica se llevó a cabo a presión atmosférica, en un intervalo de temperatura de 350-500°C, utilizando una relación molar estequiométrica de CO₂/H₂. Los resultados más sobresalientes se obtuvieron con los catalizadores 20%/NiZrO₂-COM y 20%/NiZrO₂-COP con conversiones de CO2 cercanas al 50% a temperaturas de 400°C. El catalizador 20%/NiZrO₂-COP presentó una buena estabilidad con una caída en la conversión de solo el 8% a un tiempo de corrida experimental de 200 horas.In this work the effect of synthesis method for ZrO₂ as support, and the effect of metal loading on the catalytic hydrogenation of CO₂ to methane production were studied. The supports were commercial ZrO₂ (ZrO₂-COM), and zirconia synthesized by the coprecipitation (ZrO₂-COP) and the Sol-Gel (ZrO₂-SG) methods. Nickel metal loading of 10 and 20 wt. % were impregnated on the synthetized catalyst. Catalytic evaluation test was performed at atmospheric pressure conditions, in a temperature range of 350-500°C, and using a stoichiometric CO₂/H₂ molar ratio. The most outstanding results were obtained with the catalysts 20%/NiZrO₂-COM and 20%/NiZrO₂-COP with CO2 conversions close to 50% at temperatures of 400°C. The catalyst 20%/NiZrO₂-COP showed a very good stability with a decrease in CO2 conversion of only 8% after 200 hours of experimental test

Performance of genomic prediction within and across generations in maritime pine

BACKGROUND: Genomic selection (GS) is a promising approach for decreasing breeding cycle length in forest trees. Assessment of progeny performance and of the prediction accuracy of GS models over generations is therefore a key issue.[br/] [br/] RESULTS: A reference population of maritime pine (Pinus pinaster) with an estimated effective inbreeding population size (status number) of 25 was first selected with simulated data. This reference population (n = 818) covered three generations (G0, G1 and G2) and was genotyped with 4436 single-nucleotide polymorphism (SNP) markers. We evaluated the effects on prediction accuracy of both the relatedness between the calibration and validation sets and validation on the basis of progeny performance. Pedigree-based (best linear unbiased prediction, ABLUP) and marker-based (genomic BLUP and Bayesian LASSO) models were used to predict breeding values for three different traits: circumference, height and stem straightness. On average, the ABLUP model outperformed genomic prediction models, with a maximum difference in prediction accuracies of 0.12, depending on the trait and the validation method. A mean difference in prediction accuracy of 0.17 was found between validation methods differing in terms of relatedness. Including the progenitors in the calibration set reduced this difference in prediction accuracy to 0.03. When only genotypes from the G0 and G1 generations were used in the calibration set and genotypes from G2 were used in the validation set (progeny validation), prediction accuracies ranged from 0.70 to 0.85.[br/] [br/] CONCLUSIONS: This study suggests that the training of prediction models on parental populations can predict the genetic merit of the progeny with high accuracy: an encouraging result for the implementation of GS in the maritime pine breeding program

Procesos de diálogo para la formulación de políticas de CTI en América Latina y España

Este trabajo forma parte de un esfuerzo más amplia de reflexión sobre Ciencia, Tecnología y Sociedad en América Latina, que viene desarrollando el Grupo de trabajo Ciencia y Sociedad de CLACSO. En particular, este libro contribuye a alimentar el pensamiento en torno a la generación de políticas de CTI basadas en la evidencia, a partir de la discusión de estudios de caso sobre los procesos de diálogo de las comunidades para construir política pública. Esperamos que la recopilación de estos casos de estudios, estructurados a través del marco analítico que proponemos, sean considerados como un aporte a la construcción de políticas públicas de CTI, basadas en la participación pública, que logren contribuir al desarrollo de ALC y España. De la Presentación de Gabriela Dutrénit y José Miguel Natera

Performance of genomic prediction within and across generations in maritime pine

BACKGROUND: Genomic selection (GS) is a promising approach for decreasing breeding cycle length in forest trees. Assessment of progeny performance and of the prediction accuracy of GS models over generations is therefore a key issue. RESULTS: A reference population of maritime pine (Pinus pinaster) with an estimated effective inbreeding population size (status number) of 25 was first selected with simulated data. This reference population (n = 818) covered three generations (G0, G1 and G2) and was genotyped with 4436 single-nucleotide polymorphism (SNP) markers. We evaluated the effects on prediction accuracy of both the relatedness between the calibration and validation sets and validation on the basis of progeny performance. Pedigree-based (best linear unbiased prediction, ABLUP) and marker-based (genomic BLUP and Bayesian LASSO) models were used to predict breeding values for three different traits: circumference, height and stem straightness. On average, the ABLUP model outperformed genomic prediction models, with a maximum difference in prediction accuracies of 0.12, depending on the trait and the validation method. A mean difference in prediction accuracy of 0.17 was found between validation methods differing in terms of relatedness. Including the progenitors in the calibration set reduced this difference in prediction accuracy to 0.03. When only genotypes from the G0 and G1 generations were used in the calibration set and genotypes from G2 were used in the validation set (progeny validation), prediction accuracies ranged from 0.70 to 0.85. CONCLUSIONS: This study suggests that the training of prediction models on parental populations can predict the genetic merit of the progeny with high accuracy: an encouraging result for the implementation of GS in the maritime pine breeding program

Outcomes in Newly Diagnosed Atrial Fibrillation and History of Acute Coronary Syndromes: Insights from GARFIELD-AF

BACKGROUND: Many patients with atrial fibrillation have concomitant coronary artery disease with or without acute coronary syndromes and are in need of additional antithrombotic therapy. There are few data on the long-term clinical outcome of atrial fibrillation patients with a history of acute coronary syndrome. This is a 2-year study of atrial fibrillation patients with or without a history of acute coronary syndromes