Regional Science trends through the analysis of the main facts of the 51st ERSA Conference

The 51st ERSA Conference held in Barcelona in 2011 was one of the largest ever. By examining the characteristics of the conference, this paper identifies the main trends in Regional Science and draws on a broad array of sources of information: the delegates" demographic details, the conference program itself, a satisfaction survey conducted among delegates, a quality survey addressed to those chairing the sessions and, finally, a bibliometric database including each author signing a paper presented at the conference. We finally run a regression analysis from which we show that for ERSA delegates what matters most is quality, and this must be the direction that future conferences should move toward. Ultimately, ERSA conferences are comprehensive, all-embracing occasions, representing an ideal opportunity for regional scientists to present their work to each other and to network.

The environmental effects of changing speed limits: a quantile regression approach

Two speed management policies were implemented in the metropolitan area of Barcelona aimed at reducing air pollution concentration levels. In 2008, the maximum speed limit was reduced to 80 km/h and, in 2009, a variable speed system was introduced on some metropolitan motorways. This paper evaluates whether such policies have been successful in promoting cleaner air, not only in terms of mean pollutant levels but also during high and low pollution episodes. We use a quantile regression approach for fixed effect panel data. We find that the variable speed system improves air quality with regard to the two pollutants considered here, being most effective when nitrogen oxide levels are not too low and when particulate matter concentrations are below extremely high levels. However, reducing the maximum speed limit from 120/100 km/h to 80 km/h has no effect – or even a slightly increasing effect –on the two pollutants, depending on the pollution scenario. Length: 32 pages

A Hierarchical Approach for Multi-task Logistic Regression

Peer-reviewed

Analysis of laboratory intercomparison data: a matter of independence

When laboratory intercomparison exercises are conducted, there is no a priori dependence of the concentration of a certain compound determined in one laboratory to that determined by another(s). The same applies when comparing different methodologies. A existing data set of total mercury readings in fish muscle samples involved in a Brazilian intercomparison exercise was used to show that correlation analysis is the most effective statistical tool in this kind of experiments. Problems associated with alternative analytical tools such as mean or paired 't'-test comparison and regression analysis are discussed.

Financial stress transmission in EMU sovereign bond market volatility: a connectedness analysis

This paper measures the connectedness in EMU sovereign market volatility between April 1999 and January 2014, in order to monitor stress transmission and to identify episodes of intensive spillovers from one country to the others. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach) using a framework recently proposed by Diebold and Yılmaz (2014). Second, we make use of a dynamic analysis to evaluate the net directional connectedness for each country and apply panel model techniques to investigate its determinants. Finally, to gain further insights, we examine the timevarying behaviour of net pair-wise directional connectedness at different stages of the recent sovereign debt crisis.

Automatic evaluation and data generation for analytical chemistry instrumental analysis exercises

In general, laboratory activities are costly in terms of time, space, and money. As such, the ability to provide realistically simulated laboratory data that enables students to practice data analysis techniques as a complementary activity would be expected to reduce these costs while opening up very interesting possibilities. In the present work, a novel methodology is presented for design of analytical chemistry instrumental analysis exercises that can be automatically personalized for each student and the results evaluated immediately. The proposed system provides each student with a different set of experimental data generated randomly while satisfying a set of constraints, rather than using data obtained from actual laboratory work. This allows the instructor to provide students with a set of practical problems to complement their regular laboratory work along with the corresponding feedback provided by the system's automatic evaluation process. To this end, the Goodle Grading Management System (GMS), an innovative web-based educational tool for automating the collection and assessment of practical exercises for engineering and scientific courses, was developed. The proposed methodology takes full advantage of the Goodle GMS fusion code architecture. The design of a particular exercise is provided ad hoc by the instructor and requires basic Matlab knowledge. The system has been employed with satisfactory results in several university courses. To demonstrate the automatic evaluation process, three exercises are presented in detail. The first exercise involves a linear regression analysis of data and the calculation of the quality parameters of an instrumental analysis method. The second and third exercises address two different comparison tests, a comparison test of the mean and a t-paired test.

Analysis of Patterns in Electricity Spot Market Time Series

Due to its non-storability, electricity must be produced at the same time that it is consumed, as a result prices are determined on an hourly basis and thus analysis becomes more challenging. Moreover, the seasonal fluctuations in demand and supply lead to a seasonal behavior of electricity spot prices. The purpose of this thesis is to seek and remove all causal effects from electricity spot prices and remain with pure prices for modeling purposes. To achieve this we use Qlucore Omics Explorer (QOE) for the visualization and the exploration of the data set and Time Series Decomposition method to estimate and extract the deterministic components from the series. To obtain the target series we use regression based on the background variables (water reservoir and temperature). The result obtained is three price series (for Sweden, Norway and System prices) with no apparent pattern.

Automated static image analysis as a novel tool in describing the physical properties of dietary fiber

Abstract The growing interest in the usage of dietary fiber in food has caused the need to provide precise tools for describing its physical properties. This research examined two dietary fibers from oats and beets, respectively, in variable particle sizes. The application of automated static image analysis for describing the hydration properties and particle size distribution of dietary fiber was analyzed. Conventional tests for water holding capacity (WHC) were conducted. The particles were measured at two points: dry and after water soaking. The most significant water holding capacity (7.00 g water/g solid) was achieved by the smaller sized oat fiber. Conversely, the water holding capacity was highest (4.20 g water/g solid) in larger sized beet fiber. There was evidence for water absorption increasing with a decrease in particle size in regards to the same fiber source. Very strong correlations were drawn between particle shape parameters, such as fiber length, straightness, width and hydration properties measured conventionally. The regression analysis provided the opportunity to estimate whether the automated static image analysis method could be an efficient tool in describing the hydration properties of dietary fiber. The application of the method was validated using mathematical model which was verified in comparison to conventional WHC measurement results.

Statistical Analysis of Diabetes Mellitus

Diabetes mellitus is a disease where the glucosis-content of the blood does not automatically decrease to a ”normal” value between 70 mg/dl and 120 mg/dl (3,89 mmol/l and 6,67 mmol/l) between perhaps one hour (or two hours) after eating. Several instruments can be used to arrive at a relative low increase of the glucosis-content. Besides drugs (oral antidiabetica, insulin) the blood-sugar content can mainly be influenced by (i) eating, i.e., consumption of the right amount of food at the right time (ii) physical training (walking, cycling, swimming). In a recent paper the author has performed a regression analysis on the influence of eating during the night. The result was that one ”bread-unit” (12g carbon-hydrats) increases the blood-sugar by about 50 mg/dl, while one hour after eating the blood-sugar decreases by about 10 mg/dl per hour. By applying this result-assuming its correctness - it is easy to eat the right amount during the night and to arrive at a fastening blood-sugar (glucosis-content) in the morning of about 100 mg/dl (5,56 mmol/l). In this paper we try to incorporate some physical exercise into the model.

Factores de riesgo para sobrepeso y obesidad en escolares en una población bogotana

Introducción: con las recientes tendencias de estilo de vida, no está claro qué factores son los contribuyentes más importantes en niños escolares para desarrollar sobrepeso- obesidad. Objetivo. Evaluar el impacto de los factores prenatales, perinatales y ambientales sobre el desarrollo de sobrepeso y obesidad en niños de 5 a 10 años en una población bogotana. Materiales y métodos: se realizó un estudio de casos y controles no pareado, empleando una encuesta a 528 niños, en quienes se identificaron los factores de riesgo. Se utilizó la prueba chi-cuadrado para evaluar las diferencia entre los niños normales y con sobrepeso-obesidad. Se realizó un modelo de regresión logística para evaluar los factores relevantes. Se determinaron los (OR) y sus intervalos de confianza (IC) del 95%. Resultados: se obtuvo una muestra de 528 niños. Se encontró que existen diferencias significativas en la ingesta calórica (p<0,001). El sobrepeso materno pregestacional fue de 23,2% en las madres de los casos y 16,5% en los controles (p<0,001). No hubo diferencias estadísticamente significativas con otros factores. La regresión logística arrojó datos significativos en dieta hipercalórica p =0,002 (OR =5,27; IC 95% 1,79-1,54) y el peso materno p =0,005 (OR =1,03, IC 95% 1,01-1,05). Se realizó una curva ROC para el cálculo de la capacidad predictiva del modelo y el área bajo la curva es de 0.64 (IC 95% 0.59-0.69). Conclusiones: se identificó como factores de riesgo para el desarrollo de sobrepeso-obesidad infantil en niños escolares, una dieta hipercalórica y sobrepeso materno pregestacional.

Aislamiento de venas pulmonares en el Centro Internacional de Arritmias ‘Andrea Natale’ - Fundación Cardio infantil

Introducción: El Aislamiento de Venas Pulmonares (AVP) es un procedimiento de alto costo al cual son sometidos pacientes con riesgo cardiovascular elevado. Requiere un alto grado de especialización en el personal médico y paramédico que lo ejecuta, con curvas de aprendizaje que sobrepasan los dos años de formación académica y entrenamiento específico. Metodología: Se realizó un estudio de cohorte retrospectivo, donde se incluyeron 88 sujetos sometidos al procedimiento en el lapso comprendido entre el 1º de enero y el 31 de diciembre de 2013, con el objetivo de evaluar su proceso de atención en el Centro Internacional de Arritmias ‘Andrea Natale’ de la FCI – Instituto de Cardiología. Se realizó análisis de regresión lineal y logística múltiple. Resultados: Se encontró que en el 97,73%% de los pacientes el diagnóstico principal era algún tipo de Fibrilación Auricular (FA); a su vez, la comorbilidad más frecuente fue HTA en el 30,68% y ningún paciente presentaba enfermedad coronaria, no hubo diferencias significativas por sexo. La complicación peri operatoria tuvo una incidencia del 3,41%, el 22,73% requirió ingreso a UCI con un promedio de días estancia 0,25+0,51. El 98,86% de la población estudiada recibió educación pos procedimiento acerca de sus cuidados y signos de alarma. Los factores encontrados en el estudio que afectan la duración del procedimiento y la estancia hospitalaria son las interconsultas pre procedimiento, el manejo médico de la cardiomiopatía de base y el uso de anti agregantes plaquetarios pre procedimiento; los cuales, son puntos por mejorar previo al ingreso o programación del paciente para ser llevado a AVP. Discusión: Como recomendaciones específicas se destacan: La necesidad de incluir en el protocolo de preparación para ablación de venas pulmonares la realización de interconsultas a las especialidades requeridas, antes de su ingreso para la realización del procedimiento. Es importante que el paciente que lo amerite haga parte de un programa de falla cardiaca previamente al procedimiento

Curva de aprendizaje para ventana ecográfica de la vena cava inferior, en residentes de medicina de emergencias

INTRODUCCIÓN. El ultrasonido es fundamental en la medicina de emergencias, no se conoce cual debería ser la curva de aprendizaje para obtener las competencias técnicas y operativas; ACEP recomienda por cada ventana ecográfica realizar 25 repeticiones. No existe una curva de aprendizaje para ventana de VCI en la población de residentes colombianos. OBJETIVO: Determinar la curva de aprendizaje necesaria para obtener una proporción mayor al 80% de éxitos en la toma de la ventana ecográfica de la VCI, usando la escala de calificación para el aseguramiento de la calidad sugerida por ACEP, en residentes de I a III año de medicina de emergencias. METODOLOGÍA: Estudio experimental no comparativo, que evaluó la proporción de éxito en función del las tomas repetidas de la VCI por ultrasonido, mediciones que se tomaron luego de participar en una capacitación teórica y demostrativa de la técnica propuesta; se calificaron los videos según la escala publicada por ACEP. El análisis estadístico se realizó con un modelo logístico multinivel para la proporción del éxito, agrupado por repetición y agrupado por sujeto. RESULTADOS: Se obtuvo información de 8 residentes, cada uno realizo 25 repeticiones a 3 modelos sanos con asignación aleatoria. Se realizó la curva de aprendizaje obteniendo en 11 repeticiones una proporción de 0.80 (rango 0.54 a 0.92) y en 21 repeticiones una proporción de 0.9 (rango 0.75 a 0.96), datos ajustados por numero de repetición y residente. CONCLUSIÓN: La curva de aprendizaje para la ventana ecográfica de la VCI es de 11 y 21 repeticiones para obtener el 80% y 90% de éxito en residentes de medicina de emergencias de I a III año de la universidad del rosario.