Motivating Young Students to Start a Career in Nuclear: The Basic Course of Science and Nuclear Technology, An Educational Activity of Spanish Young Generation in Nuclear (JÓVENES NUCLEARES)

The main objective of this course, conducted by Jóvenes Nucleares (Spanish Young Generation in Nuclear, JJNN), a non-profit organization that depends on the Spanish Nuclear Society (SNE) is to pass on basic knowledge about Science and Nuclear Technology to the general public, mostly students and introduce them to its most relevant points. The purposes of this course are to provide general information, to answer the most common questions about Nuclear Energy and to motivate the young students to start a career in nuclear. Therefore, it is directed mainly to high school and university students, but also to general people that wants to learn about the key issues of such an important matter in our society. Anybody could attend the course, as no specific scientific education is required. The course is done at least once a year, during the Annual Meeting of the Spanish Nuclear Society, which takes place in a different Spanish city each time. The course is done also to whichever university or institution that asks for it to JJNN, with the only limit of the presenter´s availability. The course is divided into the following chapters: Physical nuclear and radiation principles, Nuclear power plants, Nuclear safety, Nuclear fuel, Radioactive waste, Decommission of nuclear facilities, Future nuclear power plants, Other uses of nuclear technology, Nuclear energy, climate change and sustainable development. The course is divided into 15 minutes lessons on the above topics, imparted by young professionals, experts in the field that belongs either to the Spanish Young Generation in Nuclear, either to companies and institutions related with nuclear energy. At the end of the course, a 200 pages book with the contents of the course is handed to every member of the audience. This book is also distributed in other course editions at high schools and universities in order to promote the scientific dissemination of the Nuclear Technology. As an extra motivation, JJNN delivers a course certificate to the assistants. At the end of the last edition course, in Santiago de Compostela, the assistants were asked to provide a feedback about it. Some really interesting lessons were learned, that will be very useful to improve next editions of the course. As a general conclusion of the courses it can be said that many of the students that have assisted to the course have increased their motivation in the nuclear field, and hopefully it will help the young talents to choose the nuclear field to develop their careers

Estudio de la influencia de los sistemas Stop/Start sobre el consumo de combustible y las emisiones de CO2 de un vehículo diesel en tráfico urbano.

Se presentan los resultados experimentales de un estudio realizado en el Laboratorio de Motores Térmicos de la ETSII de la UPM para evaluar el impacto en eficiencia energética y medioambiental de la tecnología Stop/Start en vehículos todoterreno con motor diesel, en condiciones de tráfico real urbano. Se realizaron ensayos urbanos con vehículos Land Rover Freelander2 en la zona central de la ciudad de Madrid midiendo la emisión instantánea de CO2 y de CO con equipos de medida de emisiones embarcados, y el consumo de combustible se calculó a partir del “balance de carbonos” midiendo el caudal de gases de escape mediante un caudalímetro de desarrollo propio. Se utilizaron dos vehículos todoterreno con motor diesel semejante, ambos cumpliendo los mismos límites Euro 4 para vehículos ligeros, uno convencional y otro adaptado con sistema Stop/Start. Se obtuvieron curvas de tendencia de consumo de combustible y de emisión de CO2 con la velocidad media, que demuestran el significativo efecto de mejora en la eficiencia energética de la versión de motor adaptado con sistema Stop/Start.

A collaborative filtering approach to mitigate the new user cold start problem.

The new user cold start issue represents a serious problem in recommender systems as it can lead to the loss of new users who decide to stop using the system due to the lack of accuracy in the recommenda- tions received in that first stage in which they have not yet cast a significant number of votes with which to feed the recommender system?s collaborative filtering core. For this reason it is particularly important to design new similarity metrics which provide greater precision in the results offered to users who have cast few votes. This paper presents a new similarity measure perfected using optimization based on neu- ral learning, which exceeds the best results obtained with current metrics. The metric has been tested on the Netflix and Movielens databases, obtaining important improvements in the measures of accuracy, precision and recall when applied to new user cold start situations. The paper includes the mathematical formalization describing how to obtain the main quality measures of a recommender system using leave- one-out cross validation.