La apropiación del discurso emocional, como estrategia de Jorge Eliécer Gaitán, para la movilización de masas

La presente investigación pretende analizar la apropiación del discurso emocional, como estrategia de Jorge Eliécer Gaitán, para la movilización de masas. El análisis del discurso emocional supone el estudio desde ámbitos psicológicos, sociológicos y políticos que constituyen un andamiaje diferente al de otras investigaciones hechas con base en el fenómeno “Gaitán” y a la concepción de las emociones en la movilización. Para lograr los objetivos de este estudio de caso, se realizará un análisis de fuentes primarias (discursos de Jorge Eliécer Gaitán, testimonios documentados sobre varias movilizaciones que surgieron en la época en la que el líder político era visible en las esferas del poder). Adicional a lo anterior, se realizará una revisión documental sobre las el uso del discurso emocional como estrategia para movilizar masas, influir en las decisiones de la población, crear juicios a partir de las motivaciones que la masa construía y así generar acciones concretas.

Entre el terrorismo y el terrorismo en red, un debate a propósito de los lobos solitarios en Estados Unidos (2001-2014)

El interés de esta disertación es otorgar una respuesta a la fenomenología del Lobo Solitario, que se alza como amenaza frente a los Estados, y es necesaria su correcta comprensión para poder contrarrestar sus efectos sobre la sociedad. De esta manera, se propone un debate entre los conceptos de terrorismo expuesto por un lado por Bruce Hoffman, y por el otro por Luis de la Corte Ibáñez, quienes aportarán herramientas de análisis para lograr entender la fenomenología. Para terminar proponiendo la teoría de redes, expuesta por Arquilla y Ronfeldt y Charles Perrow, como mecanismo de solución a la brecha conceptual existente, definiendo a los lobos solitarios a nivel operacional como nodos sin red, y a nivel de adoctrinamiento como redes de débil acople.

Caracterização de linhagens de soja Glycine max (L.) Merrill para produção de brotos.

2016

Productivity and chemical composition of food-type soybeans sown on different dates.

ABSTRACT. The objective of this study was to investigate the effect of different sowing dates on the yield, 100-grain weight, oil, protein and isoflavone contents of food-type soybean breeding lines UEL 110, UEL 115 and UEL 123 and a cultivar BRS 257. The materials were seeded on four sowing dates, and the experiment was conducted in a randomized block design with four replications. The productivity and 100- grain weight varied with the sowing dates and soybean genotypes. The protein content ranged from 36.40 to 42.44%, and the oil content ranged from 18.29 to 22.71%. No significant interaction was found between the genotype and sowing dates for the protein content. The isoflavone content also varied with the sowing dates and soybean genotypes. The cultivar BRS 257 had the highest isoflavone content, including the β- glucoside, malonyl glucoside and aglycones forms. The different sowing dates influenced the productivity, 100-grain weight, oil and protein content and isoflavone levels. Higher temperatures and lower rainfall during the grain filling decreased the productivity and isoflavone content and increased the protein content. For all sowing dates, the BRS 257 soybean food-type cultivar showed the highest isoflavone content, indicating that the effect of genotype is more important. Keywords: soybean, oil, protein, isoflavones. RESUMO. O objetivo deste trabalho foi investigar o efeito das diferentes épocas de semeadura na produtividade, massa de 100 grãos, teor de proteínas, óleo e isoflavonas de linhagens de soja tipo alimento UEL 110, UEL 115 e UEL 123 e cultivar BRS 257. O material foi semeado em quatro épocas de semeadura e o experimento foi conduzido em blocos casualizados com quatro repetições. A produtividade e a massa de 100 grãos variaram com a época de semeadura e com os diferentes genótipos. O teor de proteínas variou de 36,40 a 42,44% e o de óleo de 18,29 a 22,71%. Não foi encontrada interação entre genótipo e épocas de semeadura para o teor de proteínas. O teor de isoflavonas variou com as épocas de semeadura e com os genótipos. A cultivar BRS 257 apresentou maior teor de β-glicosídeos, malonil-glicosídeos e agliconas. As diferentes épocas de semeadura influenciam a produtividade, massa de 100 grãos, conteúdo de óleo, proteínas e isoflavonas. Altas temperaturas e baixas precipitações durante o enchimento dos grãos reduzem a produtividade e teor de isoflavonas e aumentam o teor de proteínas. A cultivar BRS 257 apresenta o maior teor de isoflavonas indicando que o efeito genético é mais importante.

A Proposal of process conditions for obtaining black soymilk.

2016

Comparison of multitemporal MODIS-EVI smoothing algorithms and its contribution to crop monitoring.

Crop monitoring and more generally land use change detection are of primary importance in order to analyze spatio-temporal dynamics and its impacts on environment. This aspect is especially true in such a region as the State of Mato Grosso (south of the Brazilian Amazon Basin) which hosts an intensive pioneer front. Deforestation in this region as often been explained by soybean expansion in the last three decades. Remote sensing techniques may now represent an efficient and objective manner to quantify how crops expansion really represents a factor of deforestation through crop mapping studies. Due to the special characteristics of the soybean productions' farms in Mato Grosso (area varying between 1000 hectares and 40000 hectares and individual fields often bigger than 100 hectares), the Moderate Resolution Imaging Spectroradiometer (MODIS) data with a near daily temporal resolution and 250 m spatial resolution can be considered as adequate resources to crop mapping. Especially, multitemporal vegetation indices (VI) studies have been currently used to realize this task [1] [2]. In this study, 16-days compositions of EVI (MODQ13 product) data are used. However, although these data are already processed, multitemporal VI profiles still remain noisy due to cloudiness (which is extremely frequent in a tropical region such as south Amazon Basin), sensor problems, errors in atmospheric corrections or BRDF effect. Thus, many works tried to develop algorithms that could smooth the multitemporal VI profiles in order to improve further classification. The goal of this study is to compare and test different smoothing algorithms in order to select the one which satisfies better to the demand which is classifying crop classes. Those classes correspond to 6 different agricultural managements observed in Mato Grosso through an intensive field work which resulted in mapping more than 1000 individual fields. The agricultural managements above mentioned are based on combination of soy, cotton, corn, millet and sorghum crops sowed in single or double crop systems. Due to the difficulty in separating certain classes because of too similar agricultural calendars, the classification will be reduced to 3 classes : Cotton (single crop), Soy and cotton (double crop), soy (single or double crop with corn, millet or sorghum). The classification will use training data obtained in the 2005-2006 harvest and then be tested on the 2006-2007 harvest. In a first step, four smoothing techniques are presented and criticized. Those techniques are Best Index Slope Extraction (BISE) [3], Mean Value Iteration (MVI) [4], Weighted Least Squares (WLS) [5] and Savitzky-Golay Filter (SG) [6] [7]. These techniques are then implemented and visually compared on a few individual pixels so that it allows doing a first selection between the five studied techniques. The WLS and SG techniques are selected according to criteria proposed by [8]. Those criteria are: ability in eliminating frequent noises, conserving the upper values of the VI profiles and keeping the temporality of the profiles. Those selected algorithms are then programmed and applied to the MODIS/TERRA EVI data (16-days composition periods). Tests of separability are realized based on the Jeffries-Matusita distance in order to see if the algorithms managed in improving the potential of differentiation between the classes. Those tests are realized on the overall profile (comprising 23 MODIS images) as well as on each MODIS sub-period of the profile [1]. This last test is a double interest process because it allows comparing the smoothing techniques and also enables to select a set of images which carries more information on the separability between the classes. Those selected dates can then be used to realize a supervised classification. Here three different classifiers are tested to evaluate if the smoothing techniques as a particular effect on the classification depending on the classifiers used. Those classifiers are Maximum Likelihood classifier, Spectral Angle Mapper (SAM) classifier and CHAID Improved Decision tree. It appears through the separability tests on the overall process that the smoothed profiles don't improve efficiently the potential of discrimination between classes when compared with the original data. However, the same tests realized on the MODIS sub-periods show better results obtained with the smoothed algorithms. The results of the classification confirm this first analyze. The Kappa coefficients are always better with the smoothing techniques and the results obtained with the WLS and SG smoothed profiles are nearly equal. However, the results are different depending on the classifier used. The impact of the smoothing algorithms is much better while using the decision tree model. Indeed, it allows a gain of 0.1 in the Kappa coefficient. While using the Maximum Likelihood end SAM models, the gain remains positive but is much lower (Kappa improved of 0.02 only). Thus, this work's aim is to prove the utility in smoothing the VI profiles in order to improve the final results. However, the choice of the smoothing algorithm has to be made considering the original data used and the classifier models used. In that case the Savitzky-Golay filter gave the better results.