Los estudiantes de la UNLP : Apuntes cuantitativos para una caracterización estructural

En este trabajo se presentan resultados de un relevamiento realizado a los estudiantes de la UNLP a partir de una encuesta por muestreo aleatorio. Se realiza en primer término un análisis descriptivo general sobre las principales características de dicha población, y en segundo lugar un análisis exploratorio que intenta sintetizar perfiles de los estudiantes según algunas dimensiones socio-demográficas, institucionales e ideológicas, mediante la técnica multivariada del análisis de correspondencias múltiples

Variáveis evidenciadoras dos processos de transformação do campo : O caso do Espírito Santo - Brasil

This article aims to analyze the occurrence of changes in the countryside, in Brazil, from the observation of variables such as type of job, income, family profile, access to consumer goods, services, and information and communication technology. There had been used exploratory analysis and logistic regression method, based on data from the Pesquisa Nacional de Amostra de Domicílios (Brazilian National Household Sample Survey - PNAD) for the state of Espirito Santo. The study found that about 27.2 of individuals who had lived in the countryside report an urban profile, revealing that the urban lifestyle is encompassed not only in the city

Agriculturización, inequidad distributiva y fractura del tejido social

Los cambios operados en la actividad agrícola en nuestro país a lo largo de las últimas dos décadas, identificados genéricamente bajo la denominación de agriculturización, han generado múltiples impactos, muchos de ellos de carácter contradictorio. Así, el crecimiento de la actividad económica, el incremento en los saldos exportables y en los recursos fiscales conviven, entre otras manifestaciones, con la agudización de las tensiones derivadas de la concentración económica, con nuevos impactos e incertidumbres de carácter ambiental, con desequilibrios territoriales crecientes, con la ampliación de la brecha laboral y con el incremento en la inequidad distributiva. Este trabajo presenta los resultados de un análisis exploratorio orientado a pequeñas localidades de la región pampeana, en el cual se visualiza el surgimiento de fuertes signos de fractura del tejido social, derivados del crecimiento de la inequidad distributiva de la riqueza en el interior del espacio rural. Dos tendencias fundamentales constituyen los emergentes de este proceso: 1°) los cambios en los estilos de vida de los sectores relacionados con la actividad agrícola, visibles fundamentalmente en modificaciones en las pautas de consumo (sobre todo entre los jóvenes); y 2°) la heterogeneización de las percepciones de los pobladores sobre la valorización del trabajo en la comunidad. La reconstrucción de estos procesos, escasamente abordados en la literatura académica, se realizó a través de estrategias metodológicas que combinan métodos cuanti y cualitativos, tomando como caso de estudio una pequeña localidad en la Provincia de Santa Fe

La garantía cultural como justificación en sistemas de organización de conocimiento : Aproximación crítica

Se realiza un análisis exploratorio del concepto de "garantía cultural", con el objetivo de caracterizar áreas futuras de investigación en torno al mismo. En primera instancia se analiza la noción genérica de 'garantía', tal como ha sido considerada en la Organización del Conocimiento. Se reseñan diversos tipos de garantías propuestas para legitimar la inclusión de terminología en sistemas de organización del conocimiento. Se cumple un análisis crítico del concepto de "cultura" y la manera en que distintas concepciones antropológicas, sociológicas y políticas confluyen en su construcción epistemológica. Se revisa y se problematiza el tratamiento de la garantía cultural en la literatura del área. Se valora su aporte en la construcción de identidades culturales, a través de elementos de diferenciación de la interpretación y la vivencia de la realidad. En particular se desarrolla la relación entre garantía cultural y cultura local. Se pondera la inserción del factor ético a través de la garantía cultura, en el desarrollo de esquemas de clasificación y en los procesos de clasificación e indización. Entre otras conclusiones, se establece la necesidad de explorar con mayor detenimiento las alternativas metodológicas que puedan sustentarse en esta concepción integradora y democratizadora en el ámbito de la Organización del Conocimiento

La dimensión de la subjetividad en la formación del valor inmobiliario : aplicación del método de análisis de ecuaciones estructurales al mercado residencial de Lisboa

The discretionality and the appraisers’ subjectivity that characterize traditional real estate valuation are still allowed to take part in the formation of the asset price even when respecting international standards (EVS, IVS) or Appraisal Institution´s regulations (TEGOVA, RICS, etc.). The application of econometric and statistical methods to real estate valuation aims at the elimination of subjectivity on the appraisal process. But the unanswered question underneath this subject is the following: How important is the subjective component on real estate appraisal value formation? On this study Structural Equation Models (SEM) are used to determine the importance of the objective and subjective components on real estate valuation value formation as well as the weight of economic factors and the current economic context on real estate appraisal for mortgage purposes price formation. There were used two latent variables, Objective Component and Subjective Component, witch aggregate objective observed variables and subjective observed and unobserved variables, respectively. Factorial Exploratory Analysis is the statistical technique used in order to link the observed variables extracted from the valuation appraisal reports to the latent constructs derived from the theoretical model. SEM models were used to refine the model, eliminate non‐significant variables and to determine the weight of Objective and Subjective latent variables. These techniques were applied to a sample of over 11.000 real estate assets appraisal reports throughout the time period between November of 2006 and April of 2012. The real assets used on this study are located on Lisbon’s Metropolitan Area – “Grande Lisboa” –, Portugal. From this study, we conclude that Subjective Component has a considerable weight on real estate appraisal value formation and that the external factor Economic Situation has a very small impact on real estate appraisal value formation.

Generalización de variables medioambientales mediante interpolación GIS

La investigación de esta tesis se centra en el estudio de técnicas geoestadísticas y su contribución a una mayor caracterización del binomio factores climáticos-rendimiento de un cultivo agrícola. El inexorable vínculo entre la variabilidad climática y la producción agrícola cobra especial relevancia en estudios sobre el cambio climático o en la modelización de cultivos para dar respuesta a escenarios futuros de producción mundial. Es información especialmente valiosa en sistemas operacionales de monitoreo y predicción de rendimientos de cultivos Los cuales son actualmente uno de los pilares operacionales en los que se sustenta la agricultura y seguridad alimentaria mundial; ya que su objetivo final es el de proporcionar información imparcial y fiable para la regularización de mercados. Es en este contexto, donde se quiso dar un enfoque alternativo a estudios, que con distintos planteamientos, analizan la relación inter-anual clima vs producción. Así, se sustituyó la dimensión tiempo por la espacio, re-orientando el análisis estadístico de correlación interanual entre rendimiento y factores climáticos, por el estudio de la correlación inter-regional entre ambas variables. Se utilizó para ello una técnica estadística relativamente nueva y no muy aplicada en investigaciones similares, llamada regresión ponderada geográficamente (GWR, siglas en inglés de “Geographically weighted regression”). Se obtuvieron superficies continuas de las variables climáticas acumuladas en determinados periodos fenológicos, que fueron seleccionados por ser factores clave en el desarrollo vegetativo de un cultivo. Por ello, la primera parte de la tesis, consistió en un análisis exploratorio sobre comparación de Métodos de Interpolación Espacial (MIE). Partiendo de la hipótesis de que existe la variabilidad espacial de la relación entre factores climáticos y rendimiento, el objetivo principal de esta tesis, fue el de establecer en qué medida los MIE y otros métodos geoestadísticos de regresión local, pueden ayudar por un lado, a alcanzar un mayor entendimiento del binomio clima-rendimiento del trigo blando (Triticum aestivum L.) al incorporar en dicha relación el componente espacial; y por otro, a caracterizar la variación de los principales factores climáticos limitantes en el crecimiento del trigo blando, acumulados éstos en cuatro periodos fenológicos. Para lleva a cabo esto, una gran carga operacional en la investigación de la tesis consistió en homogeneizar y hacer los datos fenológicos, climáticos y estadísticas agrícolas comparables tanto a escala espacial como a escala temporal. Para España y los Bálticos se recolectaron y calcularon datos diarios de precipitación, temperatura máxima y mínima, evapotranspiración y radiación solar en las estaciones meteorológicas disponibles. Se dispuso de una serie temporal que coincidía con los mismos años recolectados en las estadísticas agrícolas, es decir, 14 años contados desde 2000 a 2013 (hasta 2011 en los Bálticos). Se superpuso la malla de información fenológica de cuadrícula 25 km con la ubicación de las estaciones meteorológicas con el fin de conocer los valores fenológicos en cada una de las estaciones disponibles. Hecho esto, para cada año de la serie temporal disponible se calcularon los valores climáticos diarios acumulados en cada uno de los cuatro periodos fenológicos seleccionados P1 (ciclo completo), P2 (emergencia-madurez), P3 (floración) y P4 (floraciónmadurez). Se calculó la superficie interpolada por el conjunto de métodos seleccionados en la comparación: técnicas deterministas convencionales, kriging ordinario y cokriging ordinario ponderado por la altitud. Seleccionados los métodos más eficaces, se calculó a nivel de provincias las variables climatológicas interpoladas. Y se realizaron las regresiones locales GWR para cuantificar, explorar y modelar las relaciones espaciales entre el rendimiento del trigo y las variables climáticas acumuladas en los cuatro periodos fenológicos. Al comparar la eficiencia de los MIE no destaca una técnica por encima del resto como la que proporcione el menor error en su predicción. Ahora bien, considerando los tres indicadores de calidad de los MIE estudiados se han identificado los métodos más efectivos. En el caso de la precipitación, es la técnica geoestadística cokriging la más idónea en la mayoría de los casos. De manera unánime, la interpolación determinista en función radial (spline regularizado) fue la técnica que mejor describía la superficie de precipitación acumulada en los cuatro periodos fenológicos. Los resultados son más heterogéneos para la evapotranspiración y radiación. Los métodos idóneos para estas se reparten entre el Inverse Distance Weighting (IDW), IDW ponderado por la altitud y el Ordinary Kriging (OK). También, se identificó que para la mayoría de los casos en que el error del Ordinary CoKriging (COK) era mayor que el del OK su eficacia es comparable a la del OK en términos de error y el requerimiento computacional de este último es mucho menor. Se pudo confirmar que existe la variabilidad espacial inter-regional entre factores climáticos y el rendimiento del trigo blando tanto en España como en los Bálticos. La herramienta estadística GWR fue capaz de reproducir esta variabilidad con un rendimiento lo suficientemente significativo como para considerarla una herramienta válida en futuros estudios. No obstante, se identificaron ciertas limitaciones en la misma respecto a la información que devuelve el programa a nivel local y que no permite desgranar todo el detalle sobre la ejecución del mismo. Los indicadores y periodos fenológicos que mejor pudieron reproducir la variabilidad espacial del rendimiento en España y Bálticos, arrojaron aún, una mayor credibilidad a los resultados obtenidos y a la eficacia del GWR, ya que estaban en línea con el conocimiento agronómico sobre el cultivo del trigo blando en sistemas agrícolas mediterráneos y norteuropeos. Así, en España, el indicador más robusto fue el balance climático hídrico Climatic Water Balance) acumulado éste, durante el periodo de crecimiento (entre la emergencia y madurez). Aunque se identificó la etapa clave de la floración como el periodo en el que las variables climáticas acumuladas proporcionaban un mayor poder explicativo del modelo GWR. Sin embargo, en los Bálticos, países donde el principal factor limitante en su agricultura es el bajo número de días de crecimiento efectivo, el indicador más efectivo fue la radiación acumulada a lo largo de todo el ciclo de crecimiento (entre la emergencia y madurez). Para el trigo en regadío no existe ninguna combinación que pueda explicar más allá del 30% de la variación del rendimiento en España. Poder demostrar que existe un comportamiento heterogéneo en la relación inter-regional entre el rendimiento y principales variables climáticas, podría contribuir a uno de los mayores desafíos a los que se enfrentan, a día de hoy, los sistemas operacionales de monitoreo y predicción de rendimientos de cultivos, y éste es el de poder reducir la escala espacial de predicción, de un nivel nacional a otro regional. ABSTRACT This thesis explores geostatistical techniques and their contribution to a better characterization of the relationship between climate factors and agricultural crop yields. The crucial link between climate variability and crop production plays a key role in climate change research as well as in crops modelling towards the future global production scenarios. This information is particularly important for monitoring and forecasting operational crop systems. These geostatistical techniques are currently one of the most fundamental operational systems on which global agriculture and food security rely on; with the final aim of providing neutral and reliable information for food market controls, thus avoiding financial speculation of nourishments of primary necessity. Within this context the present thesis aims to provide an alternative approach to the existing body of research examining the relationship between inter-annual climate and production. Therefore, the temporal dimension was replaced for the spatial dimension, re-orienting the statistical analysis of the inter-annual relationship between crops yields and climate factors to an inter-regional correlation between these two variables. Geographically weighted regression, which is a relatively new statistical technique and which has rarely been used in previous research on this topic was used in the current study. Continuous surface values of the climate accumulated variables in specific phenological periods were obtained. These specific periods were selected because they are key factors in the development of vegetative crop. Therefore, the first part of this thesis presents an exploratory analysis regarding the comparability of spatial interpolation methods (SIM) among diverse SIMs and alternative geostatistical methodologies. Given the premise that spatial variability of the relationship between climate factors and crop production exists, the primary aim of this thesis was to examine the extent to which the SIM and other geostatistical methods of local regression (which are integrated tools of the GIS software) are useful in relating crop production and climate variables. The usefulness of these methods was examined in two ways; on one hand the way this information could help to achieve higher production of the white wheat binomial (Triticum aestivum L.) by incorporating the spatial component in the examination of the above-mentioned relationship. On the other hand, the way it helps with the characterization of the key limiting climate factors of soft wheat growth which were analysed in four phenological periods. To achieve this aim, an important operational workload of this thesis consisted in the homogenization and obtention of comparable phenological and climate data, as well as agricultural statistics, which made heavy operational demands. For Spain and the Baltic countries, data on precipitation, maximum and minimum temperature, evapotranspiration and solar radiation from the available meteorological stations were gathered and calculated. A temporal serial approach was taken. These temporal series aligned with the years that agriculture statistics had previously gathered, these being 14 years from 2000 to 2013 (until 2011 for the Baltic countries). This temporal series was mapped with a phenological 25 km grid that had the location of the meteorological stations with the objective of obtaining the phenological values in each of the available stations. Following this procedure, the daily accumulated climate values for each of the four selected phenological periods were calculated; namely P1 (complete cycle), P2 (emergency-maturity), P3 (flowering) and P4 (flowering- maturity). The interpolated surface was then calculated using the set of selected methodologies for the comparison: deterministic conventional techniques, ordinary kriging and ordinary cokriging weighted by height. Once the most effective methods had been selected, the level of the interpolated climate variables was calculated. Local GWR regressions were calculated to quantify, examine and model the spatial relationships between soft wheat production and the accumulated variables in each of the four selected phenological periods. Results from the comparison among the SIMs revealed that no particular technique seems more favourable in terms of accuracy of prediction. However, when the three quality indicators of the compared SIMs are considered, some methodologies appeared to be more efficient than others. Regarding precipitation results, cokriging was the most accurate geostatistical technique for the majority of the cases. Deterministic interpolation in its radial function (controlled spline) was the most accurate technique for describing the accumulated precipitation surface in all phenological periods. However, results are more heterogeneous for the evapotranspiration and radiation methodologies. The most appropriate technique for these forecasts are the Inverse Distance Weighting (IDW), weighted IDW by height and the Ordinary Kriging (OK). Furthermore, it was found that for the majority of the cases where the Ordinary CoKriging (COK) error was larger than that of the OK, its efficacy was comparable to that of the OK in terms of error while the computational demands of the latter was much lower. The existing spatial inter-regional variability between climate factors and soft wheat production was confirmed for both Spain and the Baltic countries. The GWR statistic tool reproduced this variability with an outcome significative enough as to be considered a valid tool for future studies. Nevertheless, this tool also had some limitations with regards to the information delivered by the programme because it did not allow for a detailed break-down of its procedure. The indicators and phenological periods that best reproduced the spatial variability of yields in Spain and the Baltic countries made the results and the efficiency of the GWR statistical tool even more reliable, despite the fact that these were already aligned with the agricultural knowledge about soft wheat crop under mediterranean and northeuropean agricultural systems. Thus, for Spain, the most robust indicator was the Climatic Water Balance outcome accumulated throughout the growing period (between emergency and maturity). Although the flowering period was the phase that best explained the accumulated climate variables in the GWR model. For the Baltic countries where the main limiting agricultural factor is the number of days of effective growth, the most effective indicator was the accumulated radiation throughout the entire growing cycle (between emergency and maturity). For the irrigated soft wheat there was no combination capable of explaining above the 30% of variation of the production in Spain. The fact that the pattern of the inter-regional relationship between the crop production and key climate variables is heterogeneous within a country could contribute to one is one of the greatest challenges that the monitoring and forecasting operational systems for crop production face nowadays. The present findings suggest that the solution may lay in downscaling the spatial target scale from a national to a regional level.

Spatially independent activity patterns in functional MRI data during the Stroop color-naming task

A method is given for determining the time course and spatial extent of consistently and transiently task-related activations from other physiological and artifactual components that contribute to functional MRI (fMRI) recordings. Independent component analysis (ICA) was used to analyze two fMRI data sets from a subject performing 6-min trials composed of alternating 40-sec Stroop color-naming and control task blocks. Each component consisted of a fixed three-dimensional spatial distribution of brain voxel values (a “map”) and an associated time course of activation. For each trial, the algorithm detected, without a priori knowledge of their spatial or temporal structure, one consistently task-related component activated during each Stroop task block, plus several transiently task-related components activated at the onset of one or two of the Stroop task blocks only. Activation patterns occurring during only part of the fMRI trial are not observed with other techniques, because their time courses cannot easily be known in advance. Other ICA components were related to physiological pulsations, head movements, or machine noise. By using higher-order statistics to specify stricter criteria for spatial independence between component maps, ICA produced improved estimates of the temporal and spatial extent of task-related activation in our data compared with principal component analysis (PCA). ICA appears to be a promising tool for exploratory analysis of fMRI data, particularly when the time courses of activation are not known in advance.

Sexual Sensation Seeking, Alcohol Use, and Risky Sexual Behavior Among Men Who Have Sex With Men

Men who have sex with men (MSM) remain most at risk for developing HIV infection. The best prevention in this population is to identify risk factors associated with unprotected sex. Recent research suggests that sexual sensation seeking (SSS) and level of average drinking moderates the relationship between drinking alcohol in the context of sex and risky sexual behavior in a young MSM population (ages 16-20). Current study is an exploratory analysis using multilevel modeling to examine if these results are consistent across a MSM population with a wider range of ages who are also heavy drinkers. Participants (n = 181) included MSM (ages 18-75 years) from a longitudinal clinical research trial. Results indicate that MSM with higher SSS were more likely to have unprotected anal sex if they drank alcohol 3 hours prior to sex than those who did not, (OR = 1.07; 95% CI: 1.03 – 1.12). There was no significant interaction effect for average levels of drinking.

El debate de la ampliación europea y los medios de comunicación publicitaria: un enfoque interdisciplinar

El objetivo central del estudio es tratar de averiguar si existen diferencias significativas entre los países miembros de la Unión Europea y los candidatos desde una perspectiva novedosa: los medios de comunicación y la publicidad. De esta forma, mediante el análisis descriptivo y el de conglomerados jerárquicos se comprueba la coherencia entre los resultados que se obtienen de este análisis y los requisitos para formar parte de la Unión. Los primeros análisis corroboran las evaluaciones efectuadas a los países candidatos y resoluciones de la Comisión. Todo ello conduce a motivar un debate sobre las implicaciones sociales y económicas, que no creativas ni éticas, del mercado publicitario y de medios en el contexto de la Unión Europea.

Transforming Health: Emerging technology, the built environment and health behaviors

Thesis (Master's)--University of Washington, 2016-06

Remotely sensed data for ecosystem analyses: Combining hierarchy and scene models

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often. constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost-benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.

Safety behaviors and dysfunctional beliefs about sleep: Testing a cognitive model of the maintenance of insomnia

Objective: Our aim was to determine if insomnia severity, dysfunctional beliefs about sleep, and depression predicted sleep-related safety behaviors. Method: Standard sleep-related measures (such as the Insomnia Severity Index; the Dysfunctional Beliefs About Sleep scale; the Depression, Anxiety, and Stress Scale; and the Sleep-Related Behaviors Questionnaire) were administered. Additionally, 14 days of sleep diary (Pittsburg Sleep Diary) data and actual use of sleep-related behaviors were collected. Results: Regression analysis revealed that dysfunctional beliefs about sleep predicted sleep-related safety behaviors. Insomnia severity did not predict sleep-related safety behaviors. Depression accounted for the greatest amount of unique variance in the prediction of safety behaviors, followed by dysfunctional beliefs. Exploratory analysis revealed that participants with higher levels of depression used more sleep-related behaviors and reported greater dysfunctional beliefs about their sleep. Conclusion: The findings underlie the significant influence that dysfunctional beliefs have on individuals' behaviors. Moreover, the results suggest that depression may need to be considered as an explicit component of cognitive-behavioral models of insomnia. (c) 2006 Elsevier Inc. All rights reserved.

A TECNOLOGIA MÓVEL E OS POTENCIAIS DA COMUNICAÇÃO NA EDUCAÇÃO

A pesquisa é baseada em três eixos principais, comunicação, educação e tecnologias digitais, com uma análise exploratória do mercado de produção de conteúdos para mídias móveis. O estudo é desenvolvido com revisão bibliográfica referente a esses três eixos e com o uso da metodologia qualitativa. São realizadas entrevistas semi-estruturadas com representantes do mercado de comunicação móvel do país, com o objetivo de descrever o fluxo de produção de conteúdos, com foco nas possibilidades de desenvolvimento da aprendizagem móvel. Neste sentido, são verificados os potenciais tecnológicos e comunicacionais do uso das novas Tecnologias da Informação e da Comunicação (TIC), com destaque para o celular, nos modelos de educação formal e informal, a partir de aspectos da Sociedade do Conhecimento, como convergência de mídias, interatividade e produção colaborativa. Observa-se tendências como a valorização do conteúdo em relação aos meios de comunicação e o desenvolvimento de novas experiências de acesso à informação com o uso das tecnologias móveis e convergentes.

Data visualisation with missing data: A non-linear approach

Exploratory analysis of data in all sciences seeks to find common patterns to gain insights into the structure and distribution of the data. Typically visualisation methods like principal components analysis are used but these methods are not easily able to deal with missing data nor can they capture non-linear structure in the data. One approach to discovering complex, non-linear structure in the data is through the use of linked plots, or brushing, while ignoring the missing data. In this technical report we discuss a complementary approach based on a non-linear probabilistic model. The generative topographic mapping enables the visualisation of the effects of very many variables on a single plot, which is able to incorporate far more structure than a two dimensional principal components plot could, and deal at the same time with missing data. We show that using the generative topographic mapping provides us with an optimal method to explore the data while being able to replace missing values in a dataset, particularly where a large proportion of the data is missing.

Block GTM: Incorporating prior knowledge of covariance structure in data visualisation

Visualising data for exploratory analysis is a big challenge in scientific and engineering domains where there is a need to gain insight into the structure and distribution of the data. Typically, visualisation methods like principal component analysis and multi-dimensional scaling are used, but it is difficult to incorporate prior knowledge about structure of the data into the analysis. In this technical report we discuss a complementary approach based on an extension of a well known non-linear probabilistic model, the Generative Topographic Mapping. We show that by including prior information of the covariance structure into the model, we are able to improve both the data visualisation and the model fit.