Variables que influyen en la deserción de estudiantes universitarios de primer año. Construcción de índices de riesgo de abandono.

El presente artículo se enfoca en analizar la relación que existe entre la deserción de los estudios universitarios (durante el primer año cursado) y el comportamiento de ciertas variables específicas, medidas en los ingresantes a la Universidad Siglo 21 en Córdoba, Argentina. La investigación permitió desarrollar dos modelos de predicción del riesgo de abandono entre los estudiantes que ingresan a la universidad. Dichos modelos se denominan IRAP (Índice de Riesgo de Abandono Provisorio) e IRAD (Índice de Riesgo de Abandono Definitivo). Ambos se expresan en escalas de 5 categorías (desde riesgo muy bajo a muy alto). Los dos índices de riesgo se obtienen a partir de la aplicación de una serie de cuestionarios que miden diferentes variables con las cuales se construyen el IRAP y el IRAD. Ambos índices han sido desarrollados con el propósito de contar con herramientas de predicción de la deserción, lo cual permite trabajar sobre la prevención de la misma de modo anticipado. Entre las principales conclusiones que se obtuvieron en la investigación pueden señalarse la relación del rendimiento académico con la deserción y la capacidad predictiva del índice IRAD, dado que se observa que el 44% de los alumnos con riesgo alto y muy alto, no se reinscribieron en el segundo semestre de cursado.

Aplicación de redes de datos inalámbricas al control del medio ambiente de invernadero para el manejo de variables productivas en cultivos ornamentales.

Este proyecto interdisciplinario consiste en la implementación y aplicación de una red inalámbrica sobre el manejo intensivo del medio-ambiente en cultivos ornamentales. Las especies elegidas para dicha implementación y aplicación son: Lilium spp. y Solidago spp. La red inalámbrica para la transmisión de datos digitales se instalará en un ambiente de invernadero automatizado donde dispositivos inalámbricos se integrarán en una red inteligente para la transmisión de datos por radio frecuencia. Además se podrá vizualizar por Internet. Con el proyecto se pretende el estudio y caracterización del ambiente para una posterior actuación sobre el mismo. Con esto se espera dar respuestas al comportamiento de los cultivos ornamentales frente a parámetros ambientales en un esquema de producción eficiente. Los resultados obtenidos, en el medio ambiente del centro de nuestra provincia de Córdoba, tendrá la transferencia tecnológica correspondiente al sector productivo.

Desarrollo de modelos de predicción de rendimiento de cultivos para fertilización con dosis óptimas económicas y variables de nitrógeno por sitios, mediante aplicaciones de percepción remota.

Objetivo General: Desarrollar modelos de predicción de rendimiento de cultivos para refertilización con dosis óptimas económicas y variables de nitrógeno por sitios dentro del lote, mediante aplicaciones de percepción remota. Específicos: 1) Determinar la relación de la respuesta espectral del cultivo de maíz durante el desarrollo vegetativo con su rendimiento; 2) Generar dosis óptimas económicas y variables de nitrógeno (N) específicas por sitios dentro del lote; 3) Evaluar el rendimiento, la eficiencia del uso de N (EUN) y la rentabilidad de fertilizaciones fijas versus variables.

Asociación de variables cognitivas y actitudinales con la deserción en alumnos universitarios ingresantes.

La deserción en primer año de la Universidad es el resultado de un proceso complejo en el que participan numerosas variables. En este estudio se toman algunas de las variables más determinantes del abandono de estudios, las cuales se miden en alumnos ingresantes a la UE. Estas variables son: las habilidades cognitivas verbales, variables referentes a la personalidad, tales como la responsabilidad; un tercer grupo referido a las características sociodemográficas y, como variable conductual, el rendimiento académico de los alumnos en el primer semestre de cursado. El objetivo general de la investigación es relacionar estadísticamente estas variables con la deserción y construir un índice de riesgo de abandono provisorio, para luego poder generar estrategias de retención preventivas, prematuras y eficientes. Para la medición de las variables mencionadas se aplica un test de habilidades cognitivas verbales (DAT se ha desarrollado y aplicado un nuevo instrumento (CPA), y se ha construido un indicador de rendimiento académico. Por último, en función del perfil de respuestas de los alumnos, agrupándolos por análisis estadísticos multivariados, se obtuvieron clusters o grupos de alumnos que responden de modo similar a los cuestionarios e instrumentos administrados. Estos grupos de alumnos tienen características comunes que permiten identificarlos y atender a su perfil para generar estrategias de retención grupales. Se identificaron cuatro clusters y se describieron sus características distintivas.

DESARROLLO DE APLICACIONES ESTADÍSTICAS PARA LA AGRICULTURA DE PRECISIÓN. STATISTICAL APPLICATIONS FOR PRECISION AGRICULTURE

A partir de las últimas décadas se ha impulsado el desarrollo y la utilización de los Sistemas de Información Geográficos (SIG) y los Sistemas de Posicionamiento Satelital (GPS) orientados a mejorar la eficiencia productiva de distintos sistemas de cultivos extensivos en términos agronómicos, económicos y ambientales. Estas nuevas tecnologías permiten medir variabilidad espacial de propiedades del sitio como conductividad eléctrica aparente y otros atributos del terreno así como el efecto de las mismas sobre la distribución espacial de los rendimientos. Luego, es posible aplicar el manejo sitio-específico en los lotes para mejorar la eficiencia en el uso de los insumos agroquímicos, la protección del medio ambiente y la sustentabilidad de la vida rural. En la actualidad, existe una oferta amplia de recursos tecnológicos propios de la agricultura de precisión para capturar variación espacial a través de los sitios dentro del terreno. El óptimo uso del gran volumen de datos derivado de maquinarias de agricultura de precisión depende fuertemente de las capacidades para explorar la información relativa a las complejas interacciones que subyacen los resultados productivos. La covariación espacial de las propiedades del sitio y el rendimiento de los cultivos ha sido estudiada a través de modelos geoestadísticos clásicos que se basan en la teoría de variables regionalizadas. Nuevos desarrollos de modelos estadísticos contemporáneos, entre los que se destacan los modelos lineales mixtos, constituyen herramientas prometedoras para el tratamiento de datos correlacionados espacialmente. Más aún, debido a la naturaleza multivariada de las múltiples variables registradas en cada sitio, las técnicas de análisis multivariado podrían aportar valiosa información para la visualización y explotación de datos georreferenciados. La comprensión de las bases agronómicas de las complejas interacciones que se producen a la escala de lotes en producción, es hoy posible con el uso de éstas nuevas tecnologías. Los objetivos del presente proyecto son: (l) desarrollar estrategias metodológicas basadas en la complementación de técnicas de análisis multivariados y geoestadísticas, para la clasificación de sitios intralotes y el estudio de interdependencias entre variables de sitio y rendimiento; (ll) proponer modelos mixtos alternativos, basados en funciones de correlación espacial de los términos de error que permitan explorar patrones de correlación espacial de los rendimientos intralotes y las propiedades del suelo en los sitios delimitados. From the last decades the use and development of Geographical Information Systems (GIS) and Satellite Positioning Systems (GPS) is highly promoted in cropping systems. Such technologies allow measuring spatial variability of site properties including electrical conductivity and others soil features as well as their impact on the spatial variability of yields. Therefore, site-specific management could be applied to improve the efficiency in the use of agrochemicals, the environmental protection, and the sustainability of the rural life. Currently, there is a wide offer of technological resources to capture spatial variation across sites within field. However, the optimum use of data coming from the precision agriculture machineries strongly depends on the capabilities to explore the information about the complex interactions underlying the productive outputs. The covariation between spatial soil properties and yields from georeferenced data has been treated in a graphical manner or with standard geostatistical approaches. New statistical modeling capabilities from the Mixed Linear Model framework are promising to deal with correlated data such those produced by the precision agriculture. Moreover, rescuing the multivariate nature of the multiple data collected at each site, several multivariate statistical approaches could be crucial tools for data analysis with georeferenced data. Understanding the basis of complex interactions at the scale of production field is now within reach the use of these new techniques. Our main objectives are: (1) to develop new statistical strategies, based on the complementarities of geostatistics and multivariate methods, useful to classify sites within field grown with grain crops and analyze the interrelationships of several soil and yield variables, (2) to propose mixed linear models to predict yield according spatial soil variability and to build contour maps to promote a more sustainable agriculture.

Desarrollo de vacunas orales basado en las propiedades protectivas y adyuvantes de las proteínas variables de superficie (VSPS) de giardia lamblia.

El protozoario parásito intestinal Giardia lamblia es el único microorganismo que coloniza el intestino superior de vertebrados, incluyendo al hombre. Esto es posible porque el mismo está recubierto de una densa capa protectora de proteínas ricas en cisteína que evitan la “digestión” del parásito por el pH ácido del estómago y la acción de las proteasas intestinales, llamadas VSPs por su sigla en Inglés. Nuestra hipótesis de trabajo es que estas VSPs pueden ser utilizadas para transportar antígenos vacunales para su administración por vía oral. Como se sabe, la mayoría de los agentes patógenos entran al cuerpo a través de las mucosas. Por ello, ya que las VSPs son capaces de inducir una fuerte respuesta inmune mucosal se desarrollarán diferentes estrategias para verificar su potencial utilización en formulaciones vacunales orales. Se comenzará con el modelo de Influenza y luego con otras enfermedades infecciosas de relevancia social.

Regionalización de variables hidrológicas con fines de diseño de obras de infraestructura y manejo integrado de cuencas.

Las relaciones intensidad de lluvia-duración-Recurrencia (i-d-T) y el patrón de distribución temporal de las lluvias, requeridos para estimar las "Crecientes de proyecto", empleadas para el proyecto de obras de ingeniería civil y planificación del uso del suelo, solo se pueden extraer de extensos registros de alta frecuencia, normalmente fajas pluviográficas, elemento en general no disponible en Argentina. En cambio, es habitual disponer de otro dato de lluvia provisto por pluviómetros: la lámina diaria total. Por ejemplo, solo en la provincia de Córdoba, existe información de relaciones i-d-T para siete estaciones pluviográficas, insuficientes para lograr una buena cobertura espacial de toda la Provincia. En este trabajo, se busca regionalizar las ternas i-d-T a la región central Argentina utilizando una técnica de regionalización la cual ha sido desarrollada por el EHCPA, la cual contempla el uso de un modelo predictivo e información pluviométrica la cual se caracteriza por su mayor densidad espacial. A tal fin se plasmará la información disponible en mapas digitales (grillas con resolución espacial acorde a los fines de proyecto) los cuales permiten caracterizar el comportamiento estadístico de la variable lluvia máxima diaria, a través de dos parámetros descriptivos como son la media y desvió estándar de los logaritmos de dichas series, incorporando a través de ellos características locales al modelo predictivo. Toda la información procesada y los mapas elaborados son conformados en un Sistemas de Información Geográfica (SIG).

Defining habitat characteristics influencing the distribution, density and growth of Plaice (Pleuronectes Platessa) and Dab (Limanda Limanda) on west of Ireland nursery grounds

Plaice (Pleuronectes platessa, L.) and dab (Limanda limanda, L.) are among the most abundant flatfishes in the north-eastern Atlantic region and the dominant species in shallow coastal nursery grounds. With increasing pressures on commercial flatfish stocks in combination with changing coastal environments, better knowledge of population dynamics during all life stages is needed to evaluate variability in year-class strength and recruitment to the fishery. The aim of this research was to investigate the complex interplay of biotic and abiotic habitat components influencing the distribution, density and growth of plaice and dab during the vulnerable juvenile life stage and to gain insight in spatial and temporal differences in nursery habitat quality along the west coast of Ireland. Intraspecific variability in plaice diet was observed at different spatial scales and showed a link with condition, recent growth and morphology. This highlights the effect of food availability on habitat quality and the need to consider small scale variation when attempting to link habitat quality to feeding, growth and condition of juvenile flatfish. There was evidence of trophic, spatial and temporal resource partitioning between juvenile plaice and dab allowing the co-existence of morphologically similar species in nursery grounds. In the limited survey years there was no evidence that the carrying capacity of the studied nursery grounds was reached but spatial and interannual variations in fish growth indicated fluctuating environments in terms of food availability, predator densities, sediment features and physico-chemical conditions. Predation was the most important factor affecting habitat quality for juvenile plaice and dab with crab densities negatively correlated to fish condition whereas shrimp densities were negatively associated with densities of small-sized juveniles in spring. A comparison of proxies for fish growth showed the advantage of Fulton’s K for routine use whereas RNA:DNA ratios proved less powerful when short-term environmental fluctuations are lacking. This study illustrated how distinct sets of habitat features can drive spatial variation in density and condition of juvenile flatfish highlighting the value of studying both variables when modeling habitat requirements. The habitat models generated in this study also provide a powerful tool to predict potential climate and anthropogenic impacts on the distribution and condition of juveniles in flatfish nurseries. The need for effective coastal zone management was emphasized to ensure a sustainable use of coastal resources and successful flatfish recruitment to the fishery.

Insulin Resistance, Dyslipidemia and Cardiovascular Changes in a Group of Obese Children

Introduction: Obesity-related comorbidities are present in young obese children, providing a platform for early adult cardiovascular disorders. Objectives: To compare and correlate markers of adiposity to metabolic disturbances, vascular and cardiac morphology in a European pediatric obese cohort. Methods: We carried out an observational and transversal analysis in a cohort consisting of 121 obese children of both sexes, between the ages of 6 and 17 years. The control group consisted of 40 children with normal body mass index within the same age range. Markers of adiposity, plasma lipids and lipoproteins, homeostasis model assessment-insulin resistance, common carotid artery intima-media thickness and left ventricular diameters were analyzed. Results: There were statistically significant differences between the control and obese groups for the variables analyzed, all higher in the obese group, except for age, high-density lipoprotein cholesterol and adiponectin, higher in the control group. In the obese group, body mass index was directly correlated to left ventricular mass (r=0.542; p=0.001), the homeostasis model assessment-insulin resistance (r=0.378; p=<0.001) and mean common carotid artery intima-media thickness (r=0.378; p=<0.001). In that same group, insulin resistance was present in 38.1%, 12.5% had a combined dyslipidemic pattern, and eccentric hypertrophy was the most common left ventricular geometric pattern. Conclusions: These results suggest that these markers may be used in clinical practice to stratify cardiovascular risk, as well as to assess the impact of weight control programs.

Metabolic Syndrome and Importance of Associated Variables in Children and Adolescents in Guabiruba - SC, Brazil

Background:The risk factors that characterize metabolic syndrome (MetS) may be present in childhood and adolescence, increasing the risk of cardiovascular disease in adulthood.Objective:Evaluate the prevalence of MetS and the importance of its associated variables, including insulin resistance (IR), in children and adolescents in the city of Guabiruba-SC, Brazil.Methods:Cross-sectional study with 1011 students (6–14 years, 52.4% girls, 58.5% children). Blood samples were collected for measurement of biochemical parameters by routine laboratory methods. IR was estimated by the HOMA-IR index, and weight, height, waist circumference and blood pressure were determined. Multivariate logistic regression models were used to examine the associations between risk variables and MetS.Results:The prevalence of MetS, IR, overweight and obesity in the cohort were 14%, 8.5%, 21% and 13%, respectively. Among students with MetS, 27% had IR, 33% were overweight, 45.5% were obese and 22% were eutrophic. IR was more common in overweight (48%) and obese (41%) students when compared with eutrophic individuals (11%; p = 0.034). The variables with greatest influence on the development of MetS were obesity (OR = 32.7), overweight (OR = 6.1), IR (OR = 4.4; p ≤ 0.0001 for all) and age (OR = 1.15; p = 0.014).Conclusion:There was a high prevalence of MetS in children and adolescents evaluated in this study. Students who were obese, overweight or insulin resistant had higher chances of developing the syndrome.

Left Atrial Volume Determinants in Patients with Non-Ischemic Dilated Cardiomyopathy

Background:Left atrial volume (LAV) is a predictor of prognosis in patients with heart failure.Objective:We aimed to evaluate the determinants of LAV in patients with dilated cardiomyopathy (DCM).Methods:Ninety patients with DCM and left ventricular (LV) ejection fraction ≤ 0.50 were included. LAV was measured with real-time three-dimensional echocardiography (eco3D). The variables evaluated were heart rate, systolic blood pressure, LV end-diastolic volume and end-systolic volume and ejection fraction (eco3D), mitral inflow E wave, tissue Doppler e´ wave, E/e´ ratio, intraventricular dyssynchrony, 3D dyssynchrony index and mitral regurgitation vena contracta. Pearson´s coefficient was used to identify the correlation of the LAV with the assessed variables. A multiple linear regression model was developed that included LAV as the dependent variable and the variables correlated with it as the predictive variables.Results:Mean age was 52 ± 11 years-old, LV ejection fraction: 31.5 ± 8.0% (16-50%) and LAV: 39.2±15.7 ml/m2. The variables that correlated with the LAV were LV end-diastolic volume (r = 0.38; p < 0.01), LV end-systolic volume (r = 0.43; p < 0.001), LV ejection fraction (r = -0.36; p < 0.01), E wave (r = 0.50; p < 0.01), E/e´ ratio (r = 0.51; p < 0.01) and mitral regurgitation (r = 0.53; p < 0.01). A multivariate analysis identified the E/e´ ratio (p = 0.02) and mitral regurgitation (p = 0.02) as the only independent variables associated with LAV increase.Conclusion:The LAV is independently determined by LV filling pressures (E/e´ ratio) and mitral regurgitation in DCM.

Non-classical error bounds in the central limit theorem

The classical central limit theorem states the uniform convergence of the distribution functions of the standardized sums of independent and identically distributed square integrable real-valued random variables to the standard normal distribution function. While first versions of the central limit theorem are already due to Moivre (1730) and Laplace (1812), a systematic study of this topic started at the beginning of the last century with the fundamental work of Lyapunov (1900, 1901). Meanwhile, extensions of the central limit theorem are available for a multitude of settings. This includes, e.g., Banach space valued random variables as well as substantial relaxations of the assumptions of independence and identical distributions. Furthermore, explicit error bounds are established and asymptotic expansions are employed to obtain better approximations. Classical error estimates like the famous bound of Berry and Esseen are stated in terms of absolute moments of the random summands and therefore do not reflect a potential closeness of the distributions of the single random summands to a normal distribution. Non-classical approaches take this issue into account by providing error estimates based on, e.g., pseudomoments. The latter field of investigation was initiated by work of Zolotarev in the 1960's and is still in its infancy compared to the development of the classical theory. For example, non-classical error bounds for asymptotic expansions seem not to be available up to now ...

Echocardiographic Predictors of Worse Outcome After Cardiac Resynchronization Therapy

Abstract Background: Cardiac resynchronization therapy (CRT) is the recommended treatment by leading global guidelines. However, 30%-40% of selected patients are non-responders. Objective: To develop an echocardiographic model to predict cardiac death or transplantation (Tx) 1 year after CRT. Method: Observational, prospective study, with the inclusion of 116 patients, aged 64.89 ± 11.18 years, 69.8% male, 68,1% in NYHA FC III and 31,9% in FC IV, 71.55% with left bundle-branch block, and median ejection fraction (EF) of 29%. Evaluations were made in the pre‑implantation period and 6-12 months after that, and correlated with cardiac mortality/Tx at the end of follow-up. Cox and logistic regression analyses were performed with ROC and Kaplan-Meier curves. The model was internally validated by bootstrapping. Results: There were 29 (25%) deaths/Tx during follow-up of 34.09 ± 17.9 months. Cardiac mortality/Tx was 16.3%. In the multivariate Cox model, EF < 30%, grade III/IV diastolic dysfunction and grade III mitral regurgitation at 6‑12 months were independently related to increased cardiac mortality or Tx, with hazard ratios of 3.1, 4.63 and 7.11, respectively. The area under the ROC curve was 0.78. Conclusion: EF lower than 30%, severe diastolic dysfunction and severe mitral regurgitation indicate poor prognosis 1 year after CRT. The combination of two of those variables indicate the need for other treatment options.

Risk Factors for Cardiovascular Disease, Metabolic Syndrome and Sleepiness in Truck Drivers

Abstract Background: Truck driver sleepiness is a primary cause of vehicle accidents. Several causes are associated with sleepiness in truck drivers. Obesity and metabolic syndrome (MetS) are associated with sleep disorders and with primary risk factors for cardiovascular diseases (CVD). We analyzed the relationship between these conditions and prevalence of sleepiness in truck drivers. Methods: We analyzed the major risk factors for CVD, anthropometric data and sleep disorders in 2228 male truck drivers from 148 road stops made by the Federal Highway Police from 2006 to 2011. Alcohol consumption, illicit drugs and overtime working hours were also analyzed. Sleepiness was assessed using the Epworth Sleepiness Scale. Results: Mean age was 43.1 ± 10.8 years. From 2006 to 2011, an increase in neck (p = 0.011) and abdominal circumference (p < 0.001), total cholesterol (p < 0.001), triglyceride plasma levels (p = 0.014), and sleepiness was observed (p < 0.001). In addition, a reduction in hypertension (39.6% to 25.9%, p < 0.001), alcohol consumption (32% to 23%, p = 0.033) and overtime hours (52.2% to 42.8%, p < 0.001) was found. Linear regression analysis showed that sleepiness correlated closely with body mass index (β = 0.19, Raj2 = 0.659, p = 0.031), abdominal circumference (β = 0.24, Raj2 = 0.826, p = 0.021), hypertension (β = -0.62, Raj2 = 0.901, p = 0.002), and triglycerides (β = 0.34, Raj2 = 0.936, p = 0.022). Linear multiple regression indicated that hypertension (p = 0.008) and abdominal circumference (p = 0.025) are independent variables for sleepiness. Conclusions: Increased prevalence of sleepiness was associated with major components of the MetS.

Association between Functional Variables and Heart Failure after Myocardial Infarction in Rats

Background: Heart failure prediction after acute myocardial infarction may have important clinical implications. Objective: To analyze the functional echocardiographic variables associated with heart failure in an infarction model in rats. Methods: The animals were divided into two groups: control and infarction. Subsequently, the infarcted animals were divided into groups: with and without heart failure. The predictive values were assessed by logistic regression. The cutoff values predictive of heart failure were determined using ROC curves. Results: Six months after surgery, 88 infarcted animals and 43 control animals were included in the study. Myocardial infarction increased left cavity diameters and the mass and wall thickness of the left ventricle. Additionally, myocardial infarction resulted in systolic and diastolic dysfunction, characterized by lower area variation fraction values, posterior wall shortening velocity, E-wave deceleration time, associated with higher values of E / A ratio and isovolumic relaxation time adjusted by heart rate. Among the infarcted animals, 54 (61%) developed heart failure. Rats with heart failure have higher left cavity mass index and diameter, associated with worsening of functional variables. The area variation fraction, the E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate were functional variables predictors of heart failure. The cutoff values of functional variables associated with heart failure were: area variation fraction < 31.18%; E / A > 3.077; E-wave deceleration time < 42.11 and isovolumic relaxation time adjusted by heart rate < 69.08. Conclusion: In rats followed for 6 months after myocardial infarction, the area variation fraction, E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate are predictors of heart failure onset.