Integración social de los refugiados guatemaltecos en México y perspectivas de retorno.

Sin resume

Influence of the stop/start system on CO2 emissions of a diesel vehicle in urban traffic

This paper presents measurements of CO2 emission and efficiency of stop/start technology on a diesel vehicle in urban traffic. Two four-wheel-drive diesel vehicles with on-board exhaust emission and vehicle activity measurement systems were tested in two urban driving circuits representative of downtown Madrid. The vehicles had similar turbocharged and intercooled diesel engines fulfilling the same Euro 4 emissions regulation; but one had an improved engine incorporating stop/start technology. CO2 emission reduction of more than 20% for the car equipped with the stop/start system was obtained. Regardless of the variability in driving style, the grade and type of streets, traffic congestion, and the engine operating temperature, the car equipped with the stop/start system has intrinsically a lower CO2 emission factor

The Environmental Attitudes and Behaviours of European Golf Tourists

Environmental attitudes and behaviours have received relatively little attention in golf tourism, compared to other tourism research areas. Golf tourism provides products and services based on nature, and they should focus on the environment. Golf has become increasingly important in the development of European tourism within the last decade. Moreover, golf is one of the primary motivations for European tourists in the sports tourism sector. This study is based on a sample of 431 golf tourists, from different nationalities, who visit Andalusia, Spain. This research examines the relationship between environmental attitudes and behavioural intentions for three subsamples of European nationalities: British, German, and Spanish. This relationship was corroborated in the three subsamples. However, the national citizenship of European golf tourists was not a moderator effect on the relationship between environmental attitudes and behavioural intentions

Value Chain: From iDMU to Shopfloor Documentation of Aeronautical Assemblies

Competition in the aerospace manufacturing companies has led them to continuously improve the efficiency of their processes from the conceptual phase to the start of production and during operation phase, providing services to clients. PLM (Product Lifecycle Management) is an end-to-end business solution which aims to provide an environment of information about the product and related processes available to the whole enterprise throughout the product’s lifecycle. Airbus designs and industrializes aircrafts using Concurrent Engineering methods since decades. The introduction of new PLM methods, procedures and tools, and the need to improve processes efficiency and reduce time-to-market, led Airbus to pursue the Collaborative Engineering method. Processes efficiency is also impacted by the variety of systems existing within Airbus. Interoperability rises as a solution to eliminate inefficiencies due to information exchange and transformations and it also provides a way to discover and reuse existing information. The ARIADNE project (Value chain: from iDMU to shopfloor documentation of aeronautical assemblies) was launched to support the industrialization process of an aerostructure by implementing the industrial Digital Mock-Up (iDMU) concept in a Collaborative Engineering framework. Interoperability becomes an important research workpackage in ARIADNE to exploit and reuse the information contained in the iDMU and to create the shop floor documentation. This paper presents the context, the conceptual approach, the methodology adopted and preliminary results of the project

Subdaily Rainfall Estimation through Daily Rainfall Downscaling Using Random Forests in Spain

Subdaily rainfall data, though essential for applications in many fields, is not as readily available as daily rainfall data. In this work, regression approaches that use atmospheric data and daily rainfall statistics as predictors are evaluated to downscale daily-to-subdaily rainfall statistics on more than 700 hourly rain gauges in Spain. We propose a new approach based on machine learning techniques that improves the downscaling skill of previous methodologies. Results are grouped by climate types (following the Köppen?Geiger classification) to investigate possible missing explanatory variables in the analysis. The methodology is then used to improve the ability of Poisson cluster models to simulate hourly rainfall series that mimic the statistical behavior of the observed ones. This approach can be applied for the study of extreme events and for daily-to-subdaily precipitation disaggregation in any location of Spain where daily rainfall data are available.This research was funded by “Agencia Estatal de Investigación (AEI)” from the Spanish Ministry of Economy, Industry and Competitiveness, and the European Regional Development Fund (ERDF) (Grant Number BIA2016-78397-P (AEI/FEDER, UE); and by Project INDECIS, which is part of ERA4CS, an ERA-NET initiated by JPIClimate and funded by FORMAS(SE), DLR (DE), BMWFW(AT), IFD(DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant Number 690462

Downscaling from daily to subdaily rainfall through regression based on large-scale atmospheric variables

Urban hydrology studies usually require observed rainfall information of high temporal resolution (1 h or less) (Smith et al., 2007) for derived flood frequency analysis, infrastructure design or risk assessments (Arnbjerg-Nielsen et al., 2013). However, rainfall stations with hourly resolution are more sparse than daily rainfall stations, and in most studies, no rainfall information is available at subdaily resolution. There are different solutions to address the problem of rainfall temporal downscaling such as the point process theory (Rodriguez-Iturbe et al., 1987) or assuming some temporal scaling behavior of the rainfall statistics (Marani and Zanetti, 2007). However, while in the first approach it is advisable to include the subdaily rainfall properties in the calibration process to improve the quality of the simulated synthetic subdaily rainfall series (Cowpertwait et al 1996), the second one is only appropriate for specific rainfall regimes or climates. The goal of the present work is to provide subdaily rainfall series at locations where only daily rainfall series are available. Our work extends the methodology carried out by Beuchat et al., 2011 to other climatic regimes. The methodology is based on seeking relationships between target subdaily rainfall statistics and available predictors, including daily rainfall statistics and large-scale atmospheric variables. Then the predicted subdaily statistics are included in the calibration process to improve the skill of the point process models to simulate synthetic subdaily series. As a result, we validate the skill of the methodology in other climatic regimes and also, in order to improve the results, we tests different regression methods and reanalysis databases. The results show the power of the methodology to simulate synthetic subdaily rainfall series.The authors would like to thank “Agencia Estatal de Investigación (AEI)‘’ from the Spanish Ministry of Economy, Industry and Competitiveness, and the European Regional Development Fund (ERDF) for the funding provided through grant BIA2016-78397-P (AEI/FEDER, UE) for the development of this work

Rammed Earth Construction: A Proposal for a Statistical Quality Control in the Execution Process

Unlike other common contemporary construction materials such as concrete, mortars, or fired clay bricks, which are widely supported by international standards and regulations, building with rammed earth is barely regulated. Furthermore, its quality control is usually problematic, which regularly encourages the rejection of this technique. In the literature, many authors have suggested ways to safely build a rammed earth wall, but only a few of them have delved into its quality control before and during the construction process. This paper introduces a preliminary methodology and establishes unified criteria, based in a statistical analysis, for both the production and the quality control of this constructive technique in cases dealing with both samples and walls

Concretion knowledge, skills and curriculum implementation level by Physical Education teacher on key competences in the province of Seville

El presente estudio tiene como objetivo establecer el grado de conocimiento, dominio y aplicación a nivel curricular del profesorado de Educación Física (EF) sobre las Competencias Básicas. Para tal investigación, se ha utilizado una metodología no manipulativa (no intervencionista), selectiva, correlacional y de encuesta. La muestra contó con la participación de 472 docentes de EF de enseñanza obligatoria de la provincia de Sevilla. La recogida de datos se hizo mediante un cuestionario ad hoc estructurado de respuesta cerrada, de escala Likert virtual de 1 a 5 y constituido por 40 ítems. Los resultados más relevantes que se obtuvieron nos muestran que dichos docentes no han alcanzado la programación y su posterior desarrollo en competencias

Optimal Phase Swapping in Low Voltage Distribution Networks Based on Smart Meter Data and Optimization Heuristics

In this paper a modified version of the Harmony Search algorithm is proposed as a novel tool for phase swapping in Low Voltage Distribution Networks where the objective is to determine to which phase each load should be connected in order to reduce the unbalance when all phases are added into the neutral conductor. Unbalanced loads deteriorate power quality and increase costs of investment and operation. A correct assignment is a direct, effective alternative to prevent voltage peaks and network outages. The main contribution of this paper is the proposal of an optimization model for allocating phases consumers according to their individual consumption in the network of low-voltage distribution considering mono and bi-phase connections using real hourly load patterns, which implies that the computational complexity of the defined combinatorial optimization problem is heavily increased. For this purpose a novel metric function is defined in the proposed scheme. The performance of the HS algorithm has been compared with classical Genetic Algorithm. Presented results show that HS outperforms GA not only on terms of quality but on the convergence rate, reducing the computational complexity of the proposed scheme while provide mono and bi phase connections.This paper includes partial results of the UPGRID project. This project has re- ceived funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 646.531), for further information check the website: http://upgrid.eu. As well as by the Basque Government through the ELKARTEK programme (BID3A and BID3ABI projects)