Hay potencial para el uso de la bicicleta

La Guía de la Movilidad Ciclista pretende proporcionar una reflexión global sobre la implantación efectiva y eficaz del modo bicicleta en el medio urbano. Se trata del proyecto de investigación PROBICI desarrollado en el marco del Plan Nacional de I+D+i 2004-2007 del CEDEX-Ministerio de Fomento, al amparo de los objetivos científicos del PEIT). Dos de sus promotores nos explican este estudio

Un dragón sin límites: la expansión de China y la evolución de la relación comercial y financiera con Argentina durante el período 1991-2014

La investigación se centra en la relación comercial y financiera entre la Argentina y China en el periodo comprendido entre 1991-2014. Para abordar el análisis se realiza una descripción de las principales características de la economía China, su expansión en América del Sur, y específicamente, en Argentina. Las variables seleccionadas, producto bruto interno, niveles de exportaciones, importaciones, balanza comercial, e inversión extranjera directa, permiten desarrollar las diferentes afirmaciones del trabajo. A lo largo del informe se puede ver con claridad como el fin de la convertibilidad marca un antes y un después en la relación entre ambas economías, pero en este trabajo no se analizará dicho acontecimiento, sino que se lo tomará como referencia

Multivariate Regression of Road Segments’ Accident Data in Italian Rural Networks

Increasing traffic flows on road infrastructures and the associated comfort and safety problems have led to an increased risk of accidents for road users. To take the proper corrective actions, it is fundamental to analyze the accident phenomenon in all its aspects. The purpose of the current paper was the development of an accident prediction model for rural road segments of Friuli-Venezia Giulia (FVG) Region. The model predicts the accident frequency as a function of Annual Average Daily Traffic (AADT), segment length, and both geometrical and environmental features related to the targeted road segment. The procedure is based on the Empirical Bayes (EB) method. The statistical model used to express the road segments’ safety was the multivariate regression structure of the Safety Performance Functions. Results of a CURE plots analysis verified that the model is highly reliable in predicting the accident dataset for AADT up to 12500 vehicles per day

Alternative Fillers in Asphalt Concrete Mixtures: Laboratory Investigation and Machine Learning Modeling towards Mechanical Performance Prediction

In recent years, due to the reduction in available natural resources, the attention of many researchers has been focused on the reuse of recycled materials and industrial waste in common engineering applications. This paper discusses the feasibility of using seven different materials as alternative fillers instead of ordinary Portland cement (OPC) in road pavement base layers: namely rice husk ash (RHA), brick dust (BD), marble dust (MD), stone dust (SD), fly ash (FA), limestone dust (LD), and silica fume (SF). To exclusively evaluate the effect that selected fillers had on the mechanical performance of asphalt mixtures, we carried out Marshall, indirect tensile strength, moisture susceptibility, and Cantabro abrasion loss tests on specimens in which only the filler type and its percentage varied while keeping constant all the remaining design parameters. Experimental findings showed that all mixtures, except those prepared with 4% RHA or MD, met the requirements of Indian standards with respect to air voids, Marshall stability and quotient. LD and SF mixtures provided slightly better mechanical strength and durability than OPC ones, proving they can be successfully recycled as filler in asphalt mixtures. Furthermore, a Machine Learning methodology based on laboratory results was developed. A decision tree Categorical Boosting approach allowed the main mechanical properties of the investigated mixtures to be predicted on the basis of the main compositional variables, with a mean Pearson correlation and a mean coefficient of determination equal to 0.9724 and 0.9374, respectively

Volumetric Properties and Stiffness Modulus of Asphalt Concrete Mixtures Made with Selected Quarry Fillers: Experimental Investigation and Machine Learning Prediction

In recent years, the attention of many researchers in the field of pavement engineering has focused on the search for alternative fillers that could replace Portland cement and traditional limestone in the production of asphalt mixtures. In addition, from a Czech perspective, there was the need to determine the quality of asphalt mixtures prepared with selected fillers provided by different local quarries and suppliers. This paper discusses an experimental investigation and a machine learning modeling carried out by a decision tree CatBoost approach, based on experimentally determined volumetric and mechanical properties of fine-grained asphalt concretes prepared with selected quarry fillers used as an alternative to traditional limestone and Portland cement. Air voids content and stiffness modulus at 15 °C were predicted on the basis of seven input variables, including bulk density, a categorical variable distinguishing the aggregates' quarry of origin, and five main filler-oxide contents determined by means of X-ray fluorescence spectrometry. All mixtures were prepared by fixing the filler content at 10% by mass, with a bitumen content of 6% (PG 160/220), and with roughly the same grading curve. Model predictive performance was evaluated in terms of six different evaluation metrics with Pearson correlation and coefficient of determination always higher than 0.96 and 0.92, respectively. Based on the results obtained, this study could represent a forward feasibility study on the mathematical prediction of the asphalt mixtures' mechanical behavior on the basis of its filler mineralogical composition

Possible Recycling of End-of-Life Dolomite Refractories by the Production of Geopolymer-Based Composites: Experimental Investigation

Production and characterization of geopolymers prepared by mixing metakaolin, end-of-life dolomite refractories, sodium silicate solution, and sodium hydroxide solution have been performed. The as-received refractory was crumbled in order to obtain products having, respectively, 250\ua0\u3bcm, 1 mm, and 2.5\ua0mm maximum particles size. Each batch of powder was added in different proportions to a blank geopolymeric matrix. It has been observed that the addition of waste refractory reduces workability of the reference refractory-free slurry. After hardening, only the set of samples prepared with powders with maximum size of 250\ua0\u3bcm maintain integrity while the others resulted affected by the presence of fractures caused by volumetric instabilities; samples with composition R100 showed the highest compressive strength, whereas higher refractory addition lowers strength. Specific surface area appears independent by materials composition; conversely pore volume slightly increases with the addition of dolomite refractory powder. During the thermodilatometric tests all compositions display a shrinkage of about 0.1% between 170 and 400\ua0\ub0C; however, sintering starts at higher temperature (above 600\ua0\ub0C) and samples melt in the range between 650 and 750\ua0\ub0C as a function of their composition, thus showing that the resulting materials loose refractoriness with respect to both the reference geopolymer and the dolomite refractory. Graphical Abstract: [Figure not available: see fulltext.

Road Pavement Asphalt Concretes for Thin Wearing Layers: A Machine Learning Approach towards Stiffness Modulus and Volumetric Properties Prediction

In this study a novel procedure is presented for an efficient development of predictive models of road pavement asphalt concretes mechanical characteristics and volumetric properties, using shallow artificial neural networks. The problems of properly assessing the actual generalization feature of a model and avoiding the effects induced by a fixed training-test data split are addressed. Since machine learning models require a careful definition of the network hyperparameters, a Bayesian approach is presented to set the optimal model configuration. The case study covered a set of 92 asphalt concrete specimens for thin wearing layers

Nuevo enfoque en el análisis de los factores que condicionan el uso de la bicicleta como modo de transporte urbano

La valoración del los factores que afectan al usuario a la hora de realizar su elección modal a favor de la bicicleta no es la misma que para el resto de modos. Además de algunas características peculiares, esa valoración varía de manera significativa dependiendo de la experiencia de uso de la bicicleta por parte del usuario: según si es usuario frecuente, si usa la bicicleta sólo por motivos de ocio o deporte, o si no utiliza la bicicleta. De forma general, los usuarios frecuentes dan mucha menos importancia a las barreras identificadas como fundamentales para los otros usuarios. Específicamente, la diferencia más acentuada se observa en relación a una de las barreras que más afectan a la hora de considerar la bicicleta como modo de transporte usual en la ciudad: la percepción de la peligrosidad de su uso. Mientras la mayoría de los no usuarios, y sobre todo los que sólo usan la bici para ocio o deporte, consideran muy importante o fundamental el riesgo como principal barrera al uso de la bicicleta, el factor resulta mucho menos significativo para los usuarios habituales e incluso para los usuarios ocasionales con motivo de movilidad obligada. Algo parecido resulta considerando las distancias a recorrer o la orografía como factores que llevan a usar la bicicleta menos de lo deseado. En esta línea, los usuarios que la usan para motivos de transporte urbano perciben otros factores como barreras: falta de instalaciones complementarias o climatología adversa, por ejemplo. A partir de los resultados del estudio, se propone un nuevo enfoque en la orientación de las políticas de fomento del uso urbano de la bicicleta hacia intervenciones que favorezcan la experimentación práctica de su uso en ambiente urbano, con programas dirigidos de manera especifica hacia no usuarios y usuarios por motivo de ocio o deporte. Esto puede realizarse a través de medidas que permitan el fácil acceso a las bicicletas, como la implantación de servicios de bicicleta pública, la provisión de bicicletas gratuitas para los empleados en las empresas, la rebaja de impuestos en la compra de bicicletas y su integración en el sistema de transporte publico

Road Pavement Asphalt Concretes for Thin Wearing Layers: A Machine Learning Approach towards Stiffness Modulus and Volumetric Properties Prediction

In this study a novel procedure is presented for an efficient development of predictive models of road pavement asphalt concretes mechanical characteristics and volumetric properties, using shallow artificial neural networks. The problems of properly assessing the actual generalization feature of a model and avoiding the effects induced by a fixed training-test data split are addressed. Since machine learning models require a careful definition of the network hyperparameters, a Bayesian approach is presented to set the optimal model configuration. The case study covered a set of 92 asphalt concrete specimens for thin wearing layers