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El periodismo de datos es actualmente una de las especialidades con mayor proyección en la industria. Los medios cada vez recurren más a esta especialidad para contar historias de una manera más objetiva y esto ha aumentado con la pandemia provocada por la COVID-19 debido a la gran cantidad de datos que se extraen (contagiados, vacunados, fallecidos…). Este trabajo busca descubrir los lenguajes de programación que utilizan y los casos en los que prefieren utilizar herramientas alternativas. También investiga sobre el perfil profesional y la calidad de la formación que ofrecen las universidades en España en esta modalidad. Para esto hemos realizado una entrevista a un miembro de cada medio de comunicación nacional que trabaja con los datos (n = 10). Los resultados muestran que R y Python son los más utilizados para la obtención, limpieza y análisis de los datos, mientras que JavaScript es el preferido para la visualización. En cuanto a las herramientas, las más valoradas son Excel, Google SpreadSheets y OpenRefine para la obtención, limpieza y análisis; para la visualización, predomina el uso de Datawrapper y Flourish. Finalmente se observa que las características que debe poseer un periodista que trabaja con datos son la capacidad de entrevistar a los números, entender las bases de datos y no tenerle miedo a la tecnología. La investigación refleja que en los grados de las universidades españolas no se ofrece la formación necesaria, pero que en los másteres sí que se enseñan estas habilidades. En ambos casos se tiende a ser optimistas de cara al futuro ya que cada vez se van ofreciendo más conocimientos en los grados y existe mayor oferta de másteres de esta especialización. Data journalism is considered one of the most important specialties in today’s journalism. Media outlets draw on this specialty to tell stories in a more objective and profound way. Its prominence has increased with the pandemic situation caused by COVID-19 because of the great amount of data that can be extracted (vaccinated, deceased, infected...). This study aims to explore which programming languages are frequently used and in what cases data journalists prefer employing alternative tools. This study also tries to research the professional profile required to develop this sort of contents and evaluate the quality of the professional training offered by Spanish universities on this modality. For this, we have conducted an interview with a member of every national media organizations that post data stories online (n=10). The results show that R and Python are the most used programming languages to collect the data, while JavaScript is preferred to elaborate the visualizations. In relation to the alternative tools, the most valued ones are Excel, Google Spreadsheets and OpenRefine to obtain, clean and analize data, while DataWrapper and Flourish predominate for the visualitations. Finally, we observe that the characteristics that every data journalist must possess are the ability to "interview" the numbers, understand databases and not being afraid of technology. The research reflects that Bachelor degrees don’t offer enough training, while Master’s degrees do. In both cases, the situation seems to be improving, as knowledge offered in Bachelor’s degree is growing, and there is a greater offer of master’s degrees on this specialization.

International audience; During 2017 and 2018 a second generation satellite positioning augmentation system is being demonstrated in Australia and New Zealand. This system provides Satellite Based Augmentation (SBAS) and Real TimePrecise Point Positioning (PPP) capabilities through the SBAS L1 and L5 signals broadcasted from the Inmarsat 4F1 geostationary satellite.The Australia and New Zealand SBAS and PPP testbed is promoted by Geoscience Australia (GA), Land Information New Zealand (LINZ), and the Australia and New Zealand Cooperative Research Centre for Spatial Information (CRCSI). The system is developed in collaboration with industry partners, including Lockheed Martin, Inmarsat and GMV.The services and signals broadcast during the testbed consist of: - SBAS L1 legacy service available for GPS L1 singlefrequency users over Australia and New Zealand. - SBAS DMFC L5 service available for GPS L1/L2 + GAL E1/E5a dual-frequency users over the Inmarsat 4F1 footprint. - PPP corrections through SBAS L1 message, targeting GPS L1/L2 dual-frequency users - PPP corrections through SBAS L5 message, targeting GPS L1/L2 + GAL E1/E5a dual-frequency users.The transmissions of SBAS signals started in May 2017, while the transmission of the PPP services started in October 2017.The main goal of this paper is to provide, from the point of view of the system developers, an update on the testbed service definition, infrastructure status and performances achieved during the 2017-2018 system operation.

Ceratothoa steindachneri (Isopoda: Cymothoidae) and Pentacapsula cutanea (Myxozoa: Pentacapsulidae) parasites infecting the blacktail-comber (Serranus atricauda) were considered suitable as biological tags for stock identification around the islands of La Palma and Gran Canaria, in the Western and Eastern areas of the Canarian archipelago, respectively. The ecological parameters of both species differed significantly between the islands. While individuals caught off La Palma showed a high degree of infection by the isopod, a single infected fish was found off Gran Canaria. Also, the myxozoans showed a high level of infection on fish from Gran Canaria but it was reported on only a single specimen from La Palma Ceratothoa steindachneri (Isopoda, Cymothoidae) y Pentacapsula cutanea (Myxozoa, Pentacapsulidae) se consideran marcadores biológicos adecuados para la identificación de stocks de la cabrilla (Serranus atricauda) en las islas de La Palma y Gran Canaria, en las áreas occidental y oriental del Archipiélago Canario, respectivamente. Los parámetros ecológicos para ambas especies difieren significativamente entre islas. Mientras que los peces capturados en La Palma muestran un alto grado de infestación por el isópodo, sólo se encontró un único individuo afectado por este parásito en Gran Canaria. También, el myxozoo mostró un alto nivel de infestación sobre los peces procedentes de Gran Canaria, aunque únicamente se encontró en un pez muestreado en La Palma.

Ceratothoa steindachneri (Isopoda: Cymothoidae) and Pentacapsula cutanea (Myxozoa: Pentacapsulidae) parasites infecting the blacktail-comber (Serranus atricauda) were considered suitable as biological tags for stock identification around the islands of La Palma and Gran Canaria, in the Western and Eastern areas of the Canarian archipelago, respectively. The ecological parameters of both species differed significantly between the islands. While individuals caught off La Palma showed a high degree of infection by the isopod, a single infected fish was found off Gran Canaria. Also, the myxozoans showed a high level of infection on fish from Gran Canaria but it was reported on only a single specimen from La Palma, Ceratothoa steindachneri (Isopoda, Cymothoidae) y Pentacapsula cutanea (Myxozoa, Pentacapsulidae) se consideran marcadores biológicos adecuados para la identificación de stocks de la cabrilla (Serranus atricauda) en las islas de La Palma y Gran Canaria, en las áreas occidental y oriental del Archipiélago Canario, respectivamente. Los parámetros ecológicos para ambas especies difieren significativamente entre islas. Mientras que los peces capturados en La Palma muestran un alto grado de infestación por el isópodo, sólo se encontró un único individuo afectado por este parásito en Gran Canaria. También, el myxozoo mostró un alto nivel de infestación sobre los peces procedentes de Gran Canaria, aunque únicamente se encontró en un pez muestreado en La Palma.

XI Congreso (inter)nacional de Psicología Jurídica y Forense. Granada, 1, 2 y 3 de noviembre de 2018.

En este trabajo se trata la recogida de datos subjetivos originados por las personas presentes en el accidente, una cuestión de vital importancia en la investigación de éstos y cuya exactitud depende de dos factores principales: la honestidad y la memoria de la persona que los proporciona.

Fatigue loads represent a critical element in several aeronautical applications and Wind Turbines (WTs) are not an exception. Their evolution over the machine service life usually determines its life span, hence their behavior knowledge can cause a relevant economic impact on the Cost of Energy (CoE). Nevertheless, their measurements are frequently difficult or expensive and estimations arising from other known signals can be carried out instead. This thesis aims to design a load estimation model using standard signal as inputs by means of statistical and machine learning procedures. It includes an input selection stage and the models layout arrangement and assessment, which are based on Artificial Neural Networks (ANNs). The whole process is described in the following lines. First of all, data from simulations is gathered and examined. Damage Equivalent Load (DEL) (fatigue indicator which acts as target) and stats (statistical parameters from standard signals that constitute possible model inputs) are computed and their cross relationships analyzed. Secondly, input dimensions are reduced due to their great volume. In this regard several input subsets formed by small quantities of stats are built using two different filters: Correlation (COR) and Principal Component Analysis (PCA). Once this done, each subset estimation power is compared along with a great variety of ANNs configurations. Eventually, an innovative input selection method is developed using a genetic optimization. The outcome of this process allows several observations. On one hand, estimation results seem promising as long as all of them fall below 4%. On the other hand, multilayered nets with a neurons number between 30 and 60 seem a suitable configuration for these purposes. Furthermore, the genetic optimization results also show a great performance without the necessity of the preliminary work carried out by filters (which in fact is bias ed by some a priori assumptions). To sum up, inside the wind power field -where lifespan is an important factor due to its influence on the CoE- this method may promote a more efficient usage of structural parts enhancing their service life.