Properties of seawater (partial pressure of carbon dioxide (pCO2)) from a ProOceanus CO2-Pro sensor mounted on the continuous surface water sampling system during the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides continuous measurements of partial pressure of carbon dioxide (pCO2), using a ProOceanus CO2-Pro instrument mounted on the flowthrough system. This automatic sensor is fitted with an equilibrator made of gas permeable silicone membrane and an internal detection loop with a non-dispersive infrared detector of PPSystems SBA-4 CO2 analyzer. A zero-CO2 baseline is provided for the subsequent measurements circulating the internal gas through a CO2 absorption chamber containing soda lime or Ascarite. The frequency of this automatic zero point calibration was set to be 24 hours. All data recorded during zeroing processes were discarded with the 15-minute data after each calibration. The output of CO2-Pro is the mole fraction of CO2 in the measured water and the pCO2 is obtained using the measured total pressure of the internal wet gas. The fugacity of CO2 (fCO2) in the surface seawater, whose difference with the atmospheric CO2 fugacity is proportional to the air-sea CO2 fluxes, is obtained by correcting the pCO2 for non-ideal CO2 gas concentration according to Weiss (1974). The fCO2 computed using CO2-Pro measurements was corrected to the sea surface condition by considering the temperature effect on fCO2 (Takahashi et al., 1993). The surface seawater observations that were initially estimated with a 15 seconds frequency were averaged every 5-min cycle. The performance of CO2-Pro was adjusted by comparing the sensor outputs against the thermodynamic carbonate calculation of pCO2 using the carbonic system constants of Millero et al. (2006) from the determinations of total inorganic carbon (CT ) and total alkalinity (AT ) in discrete samples collected at sea surface. AT was determined using an automated open cell potentiometric titration (Haraldsson et al. 1997). CT was determined with an automated coulometric titration (Johnson et al. 1985; 1987), using the MIDSOMMA system (Mintrop, 2005). fCO2 data are flagged according to the WOCE guidelines following Pierrot et al. (2009) identifying recommended values and questionable measurements giving additional information about the reasons of the questionability.

"Alexander von Humboldt als internationaler Publizist. Zur Edition seiner sämtlichen Schriften"

Alexander von Humboldt veröffentlichte rund 800 Aufsätze, Artikel und Essays in zahlreichen Wissensgebieten und diversen Sprachen. Die Verteilung ihrer Publikati-onsorte entspricht der Reichweite seiner Reisen und der globalen Perspektive seiner Forschungen. Die Vielfalt seiner Co-Autoren und Kooperationspartner spiegelt seine Multidisziplinarität. Humboldts umfangreiches publizistisches Werk dokumentiert sei-ne internationale Bedeutung als Wissenschaftler, Reiseschriftsteller und Kulturver-mittler. An der Universität Bern entsteht die erste Gesamtedition dieses Humboldt-schen Œuvres, die 2019 zum 250. Geburtstag des Autors vorliegen soll. Ihr Ziel ist Systematisierung, Dokumentation und Erschließung des Corpus – in einer Buchausgabe mit Text- und Apparatbänden und in einer digitalen Edition mit computerphilo-logischen Werkzeugen. Alexander von Humboldt (1769–1859), Aufsätze und Essays, internationale Publizistik, Wissenschaftsgeschichte, Editionsphilologie.

Impact of new technologies and social networks on a secondary education theatre project

This paper describes the potential impact of social media and new technologies in secondary education. The case of study has been designed for the drama and theatre subject. A wide set of tools like social networks, blogs, internet, multimedia content, local press and other promotional tools are promoted to increase students’ motivation. The experiment was developed at the highschool IES Al-Satt located in Algete in the Comunidad de Madrid. The students included in the theatre group present a low academic level, 80% of them had previously repeated at least one grade, half of them come from programs for students with learning difficulties and were at risk of social exclusion. This action is supported by higher and secondary education professors and teachers who look forward to implanting networked media technologies as new tools to improve the academic results and the degree of involvement of students. The results of the experiment have been excellent, based on satisfactory opinions obtained from a survey answered by students at the end of the course, and also revealed by the analytics taken from different social networks. This project is a pioneer in the introduction and usage of new technologies in secondary high-schools in Spain.

Energía Minihidráulica

La energía basada en turbinas hidráulicas de reducida potencia es, a menudo, un ejemplo- modelo dentro del campo de las energías renovables desde su aparición a finales del S. XIX, aunque los ingenios precursores surgen mucho antes. Entre los testimonios más antiguos destacan la saqia o rueda persa y la rueda hidráulica romana que había sido previamente implementada en Extremo Oriente, y que después llega a Europa a través de Egipto. Más tarde, durante la Edad Media y el Renacimiento, se generaliza el uso de los molinos hidráulicos, además de los eólicos. Ejemplos de ello son las norias de Alepo (Siria) y de Córdoba (España). Otro caso interesante es el de los molinos de regolfo en la Península Ibérica e Iberoamérica, muy cercanos en su forma y fundamentos a las turbinas hidráulicas. Algunos de estos ingenios siguen activos en los ríos de España. Posteriormente los estudios de Euler, Burdin y Fourneyron prepararon las bases para el definitivo avance de Pelton, Kaplan, Francis, y otros, pero ya como máquinas motrices de los generadores eléctricos. En la actualidad, se admite como límite superior para minihidráulica aquellas centrales con una potencia instalada de 5000 kW, y considerando que cuando las potencias son inferiores a 100 kW se denomina micro hidráulica, aunque en Latinoamérica este límite se fija en 20 kW. El estudio del recurso hídrico, ayudado del geotécnico, constituyen la base sobre la que podremos proyectar el aprovechamiento hidroeléctrico: selección del tipo de central dentro de la tipología disponible, diseño y cálculos de la turbina, obra civil necesaria (azud, presa, canal, tubería forzada, edificio, aspiración, desagüe, etc.) y equipo electromecánico. El proyecto tecnológico se complementa con el estudio de impacto ambiental y de viabilidad económica. Muchos de estos proyectos tratan de reducir la falta de acceso a la energía en poblaciones desfavorecidas, entendida esta carencia como un factor determinante de la pobreza. Así la energía mini y micro-hidráulica adquiere un nuevo valor como tecnología para el desarrollo humano.

p-medicine: a medical informatics platform for integrated large scale heterogeneous patient data

Secure access to patient data is becoming of increasing importance, as medical informatics grows in significance, to both assist with population health studies, and patient specific medicine in support of treatment. However, assembling the many different types of data emanating from the clinic is in itself a difficulty, and doing so across national borders compounds the problem. In this paper we present our solution: an easy to use distributed informatics platform embedding a state of the art data warehouse incorporating a secure pseudonymisation system protecting access to personal healthcare data. Using this system, a whole range of patient derived data, from genomics to imaging to clinical records, can be assembled and linked, and then connected with analytics tools that help us to understand the data. Research performed in this environment will have immediate clinical impact for personalised patient healthcare.

A study of feature combination for vehicle detection based on image processing

Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification.

Compilador de consultas tipo SQL para sistema de procesamiento masivo de eventos CEP

El paradigma de procesamiento de eventos CEP plantea la solución al reto del análisis de grandes cantidades de datos en tiempo real, como por ejemplo, monitorización de los valores de bolsa o el estado del tráfico de carreteras. En este paradigma los eventos recibidos deben procesarse sin almacenarse debido a que el volumen de datos es demasiado elevado y a las necesidades de baja latencia. Para ello se utilizan sistemas distribuidos con una alta escalabilidad, elevado throughput y baja latencia. Este tipo de sistemas son usualmente complejos y el tiempo de aprendizaje requerido para su uso es elevado. Sin embargo, muchos de estos sistemas carecen de un lenguaje declarativo de consultas en el que expresar la computación que se desea realizar sobre los eventos recibidos. En este trabajo se ha desarrollado un lenguaje declarativo de consultas similar a SQL y un compilador que realiza la traducción de este lenguaje al lenguaje nativo del sistema de procesamiento masivo de eventos. El lenguaje desarrollado en este trabajo es similar a SQL, con el que se encuentran familiarizados un gran número de desarrolladores y por tanto aprender este lenguaje no supondría un gran esfuerzo. Así el uso de este lenguaje logra reducir los errores en ejecución de la consulta desplegada sobre el sistema distribuido al tiempo que se abstrae al programador de los detalles de este sistema.---ABSTRACT---The complex event processing paradigm CEP has become the solution for high volume data analytics which demand scalability, high throughput, and low latency. Examples of applications which use this paradigm are financial processing or traffic monitoring. A distributed system is used to achieve the performance requisites. These same requisites force the distributed system not to store the events but to process them on the fly as they are received. These distributed systems are complex systems which require a considerably long time to learn and use. The majority of such distributed systems lack a declarative language in which to express the computation to perform over incoming events. In this work, a new SQL-like declarative language and a compiler have been developed. This compiler translates this new language to the distributed system native language. Due to its similarity with SQL a vast amount of developers who are already familiar with SQL will need little time to learn this language. Thus, this language reduces the execution failures at the time the programmer no longer needs to know every single detail of the underlying distributed system to submit a query.

Estudio de patrones de interacción entre los estudiantes y la Plataforma de Tele-Enseñanza en la UPM

Vivimos en una sociedad en la que la información ha adquirido una vital importancia. El uso de Internet y el desarrollo de nuevos sistemas de la información han generado un ferviente interés tanto de empresas como de instituciones en la búsqueda de nuevos patrones que les proporcione la clave del éxito. La Analítica de Negocio reúne un conjunto de herramientas, estrategias y técnicas orientadas a la explotación de la información con el objetivo de crear conocimiento útil dentro de un marco de trabajo y facilitar la optimización de los recursos tanto de empresas como de instituciones. El presente proyecto se enmarca en lo que se conoce como Gestión Educativa. Se aplicará una arquitectura y modelo de trabajo similar a lo que se ha venido haciendo en los últimos años en el entorno empresarial con la Inteligencia de Negocio. Con esta variante, se pretende mejorar la calidad de la enseñanza, agilizar las decisiones dentro de la institución académica, fortalecer las capacidades del cuerpo docente y en definitiva favorecer el aprendizaje del alumnado. Para lograr el objetivo se ha decidido seguir las etapas del Knowledge Discovery in Databases (KDD), una de las metodologías más conocidas dentro de la Inteligencia de Negocio, que describe el procedimiento que va desde la selección de la información y su carga en sistemas de almacenamiento, hasta la aplicación de técnicas de minería de datos para la obtención nuevo conocimiento. Los estudios se realizan a partir de la información de la activad de los usuarios dentro la plataforma de Tele-Enseñanza de la Universidad Politécnica de Madrid (Moodle). Se desarrollan trabajos de extracción y preprocesado de la base de datos en crudo y se aplican técnicas de minería de datos. En la aplicación de técnicas de minería de datos, uno de los factores más importantes a tener en cuenta es el tipo de información que se va a tratar. Por este motivo, se trabaja con la Minería de Datos Educativa, en inglés, Educational Data Mining (EDM) que consiste en la aplicación de técnicas de minería optimizadas para la información que se genera en entornos educativos. Dentro de las posibilidades que ofrece el EDM, se ha decidido centrar los estudios en lo que se conoce como analítica predictiva. El objetivo fundamental es conocer la influencia que tienen las interacciones alumno-plataforma en las calificaciones finales y descubrir nuevas reglas que describan comportamientos que faciliten al profesorado discriminar si un estudiante va a aprobar o suspender la asignatura, de tal forma que se puedan tomar medidas que mejoren su rendimiento. Toda la información tratada en el presente proyecto ha sido previamente anonimizada para evitar cualquier tipo de intromisión que atente contra la privacidad de los elementos participantes en el estudio. ABSTRACT. We live in a society dominated by data. The use of the Internet accompanied by developments in information systems has generated a sustained interest among companies and institutions to discover new patterns to succeed in their business ventures. Business Analytics (BA) combines tools, strategies and techniques focused on exploiting the available information, to optimize resources and create useful insight. The current project is framed under Educational Management. A Business Intelligence (BI) architecture and business models taught up to date will be applied with the aim to accelerate the decision-making in academic institutions, strengthen teacher´s skills and ultimately improve the quality of teaching and learning. The best way to achieve this is to follow the Knowledge Discovery in Databases (KDD), one of the best-known methodologies in B.I. This process describes data preparation, selection, and cleansing through to the application of purely Data Mining Techniques in order to incorporate prior knowledge on data sets and interpret accurate solutions from the observed results. The studies will be performed using the information extracted from the Universidad Politécnica de Madrid Learning Management System (LMS), Moodle. The stored data is based on the user-platform interaction. The raw data will be extracted and pre-processed and afterwards, Data Mining Techniques will be applied. One of the crucial factors in the application of Data Mining Techniques is the kind of information that will be processed. For this reason, a new Data Mining perspective will be taken, called Educational Data Mining (EDM). EDM consists of the application of Data Mining Techniques but optimized for the raw data generated by the educational environment. Within EDM, we have decided to drive our research on what is called Predictive Analysis. The main purpose is to understand the influence of the user-platform interactions in the final grades of students and discover new patterns that explain their behaviours. This could allow teachers to intervene ahead of a student passing or failing, in such a way an action could be taken to improve the student performance. All the information processed has been previously anonymized to avoid the invasion of privacy.

Análisis de ataques avanzados y sus técnicas de detección

Los ataques a redes de información son cada vez más sofisticados y exigen una constante evolución y mejora de las técnicas de detección. Para ello, en este proyecto se ha diseñado e implementado una plataforma cooperativa para la detección de intrusiones basada en red. En primer lugar, se ha realizado un estudio teórico previo del marco tecnológico relacionado con este ámbito, en el que se describe y caracteriza el software que se utiliza para realizar ataques a sistemas (malware) así como los métodos que se utilizan para llegar a transmitir ese software (vectores de ataque). En el documento también se describen los llamados APT, que son ataques dirigidos con una gran inversión económica y temporal. Estos pueden englobar todos los malware y vectores de ataque existentes. Para poder evitar estos ataques, se estudiarán los sistemas de detección y prevención de intrusiones, describiendo brevemente los algoritmos que se tienden a utilizar en la actualidad. En segundo lugar, se ha planteado y desarrollado una plataforma en red dedicada al análisis de paquetes y conexiones para detectar posibles intrusiones. Este sistema está orientado a sistemas SCADA (Supervisory Control And Data Adquisition) aunque funciona sobre cualquier red IPv4/IPv6, para ello se definirá previamente lo que es un sistema SCADA, así como sus partes principales. Para implementar el sistema se han utilizado dispositivos de bajo consumo llamados Raspberry PI, estos se ubican entre la red y el equipo final que se quiera analizar. En ellos se ejecutan 2 aplicaciones desarrolladas de tipo cliente-servidor (la Raspberry central ejecutará la aplicación servidora y las esclavas la aplicación cliente) que funcionan de forma cooperativa utilizando la tecnología distribuida de Hadoop, la cual se explica previamente. Mediante esta tecnología se consigue desarrollar un sistema completamente escalable. La aplicación servidora muestra una interfaz gráfica que permite administrar la plataforma de análisis de forma centralizada, pudiendo ver así las alarmas de cada dispositivo y calificando cada paquete según su peligrosidad. El algoritmo desarrollado en la aplicación calcula el ratio de paquetes/tiempo que entran/salen del equipo final, procesando los paquetes y analizándolos teniendo en cuenta la información de señalización, creando diferentes bases de datos que irán mejorando la robustez del sistema, reduciendo así la posibilidad de ataques externos. Para concluir, el proyecto inicial incluía el procesamiento en la nube de la aplicación principal, pudiendo administrar así varias infraestructuras concurrentemente, aunque debido al trabajo extra necesario se ha dejado preparado el sistema para poder implementar esta funcionalidad. En el caso experimental actual el procesamiento de la aplicación servidora se realiza en la Raspberry principal, creando un sistema escalable, rápido y tolerante a fallos. ABSTRACT. The attacks to networks of information are increasingly sophisticated and demand a constant evolution and improvement of the technologies of detection. For this project it is developed and implemented a cooperative platform for detect intrusions based on networking. First, there has been a previous theoretical study of technological framework related to this area, which describes the software used for attacks on systems (malware) as well as the methods used in order to transmit this software (attack vectors). In this document it is described the APT, which are attacks directed with a big economic and time inversion. These can contain all existing malware and attack vectors. To prevent these attacks, intrusion detection systems and prevention intrusion systems will be discussed, describing previously the algorithms tend to use today. Secondly, a platform for analyzing network packets has been proposed and developed to detect possible intrusions in SCADA (Supervisory Control And Data Adquisition) systems. This platform is designed for SCADA systems (Supervisory Control And Data Acquisition) but works on any IPv4 / IPv6 network. Previously, it is defined what a SCADA system is and the main parts of it. To implement it, we used low-power devices called Raspberry PI, these are located between the network and the final device to analyze it. In these Raspberry run two applications client-server developed (the central Raspberry runs the server application and the slaves the client application) that work cooperatively using Hadoop distributed technology, which is previously explained. Using this technology is achieved develop a fully scalable system. The server application displays a graphical interface to manage analytics platform centrally, thereby we can see each device alarms and qualifying each packet by dangerousness. The algorithm developed in the application calculates the ratio of packets/time entering/leaving the terminal device, processing the packets and analyzing the signaling information of each packet, reating different databases that will improve the system, thereby reducing the possibility of external attacks. In conclusion, the initial project included cloud computing of the main application, being able to manage multiple concurrent infrastructure, but due to the extra work required has been made ready the system to implement this funcionality. In the current test case the server application processing is made on the main Raspberry, creating a scalable, fast and fault-tolerant system.

Context Aware Middleware Architectures: Survey and Challenges

Abstract: Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security & privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work.

Assessing the suitability of student interactions from Moodle data logs as predictors of cross-curricular competencies

In the past decades, online learning has transformed the educational landscape with the emergence of new ways to learn. This fact, together with recent changes in educational policy in Europe aiming to facilitate the incorporation of graduate students to the labor market, has provoked a shift on the delivery of instruction and on the role played by teachers and students, stressing the need for development of both basic and cross-curricular competencies. In parallel, the last years have witnessed the emergence of new educational disciplines that can take advantage of the information retrieved by technology-based online education in order to improve instruction, such as learning analytics. This study explores the applicability of learning analytics for prediction of development of two cross-curricular competencies – teamwork and commitment – based on the analysis of Moodle interaction data logs in a Master’s Degree program at Universidad a Distancia de Madrid (UDIMA) where the students were education professionals. The results from the study question the suitability of a general interaction-based approach and show no relation between online activity indicators and teamwork and commitment acquisition. The discussion of results includes multiple recommendations for further research on this topic.