El poder económico en España : Conexiones e intereses del sector energético

Este trabajo ha tratado de analizar las redes de gobernanza empresarial existentes en España centrándose en el sector energético que, como se ha demostrado, es un sector en el cual la intensidad de las conexiones es más alta. Mediante el análisis de una muestra de cinco empresas se ha elaborado un mapa que recogiese todas las conexiones derivadas de los consejeros múltiples y la propiedad de capital y, segundo, de estudiar en qué sectores se establecen con mayor intesnsidad las conexiones. Para estudiar el otro aspecto del poder relacional, las conexiones políticas, se ha recopilado una lista de consejeros con nombres y apellidos que guardan una relación con el mundo de la política así como una recopilación de conocidos ex altos cargos políticos, como antiguos ministros y presidentes de gobierno, en esferas más bajas del gobierno corporativo.Departamento de Economía AplicadaGrado en Economí

Strategies for Attention to Diversity: Perceptions of Secondary School Teaching Staf

The authors wish to thank all the participants that took part in this investigation.(1) Background: Attention to diversity constitutes an aspect that influences system quality and offers a perspective of the capacity of educational centres to respond to educational needs. The present study carried out an examination of the perceptions held by secondary school teachers and the level of importance conferred by them to the variables that should be integrated into plans and will influence the degree of compliance. (2) Methods: Quantitative descriptive research was performed using a survey to collect data from teachers at schools that had a Quality Management System available. (3) Results: Interaction with families is necessary to agree upon the centre’s objectives to address diversity and to define an optimisation strategy for resources in virtue of their availability within the centre. It is key to establish an appropriate teacher–student ratio to encourage compliance. (4) Conclusions: Teachers are the great pillars of quality education. Their perceptions are the route through which deficient aspects and the dimensions that must be improved when formulating these strategies can be recognised with attention to diversity

AIP and MEN1 mutations and AIP immunohistochemistry in pituitary adenomas in a tertiary referral center.

Background: Pituitary adenomas have a high disease burden due to tumor growth/ invasion and disordered hormonal secretion. Germline mutations in genes such as MEN1 and AIP are associated with early onset of aggressive pituitary adenomas that can be resistant to medical therapy. Aims: We performed a retrospective screening study using published risk criteria to assess the frequency of AIP and MEN1 mutations in pituitary adenoma patients in a tertiary referral center. Methods: Pituitary adenoma patients with pediatric/adolescent onset, macroadenomas occurring ≤30 years of age, familial isolated pituitary adenoma (FIPA) kindreds and acromegaly or prolactinoma cases that were uncontrolled by medical therapy were studied genetically. We also assessed whether immunohistochemical staining for AIP (AIP-IHC) in somatotropinomas was associated with somatostatin analogs (SSA) response. Results: Fifty-five patients met the study criteria and underwent genetic screening for AIP/MEN1 mutations. No mutations were identified and large deletions/duplications were ruled out using MLPA. In a cohort of sporadic somatotropinomas, low AIP-IHC tumors were significantly larger (P = 0.002) and were more frequently sparsely granulated (P = 0.046) than high AIP-IHC tumors. No significant relationship between AIP-IHC and SSA responses was seen. Conclusions: Germline mutations in AIP/MEN1 in pituitary adenoma patients are rare and the use of general risk criteria did not identify cases in a large tertiary-referral setting. In acromegaly, low AIP-IHC was related to larger tumor size and more frequent sparsely granulated subtype but no relationship with SSA responsiveness was seen. The genetics of pituitary adenomas remains largely unexplained and AIP screening criteria could be significantly refined to focus on large, aggressive tumors in young patients

Foreword to the Special Section FORESTERRA

Foreword to the Proceedings of the Foresterra Final Conference, which was held in Lisbon, Portugal on 24-26 November 2015

Thermal emission of macroporous silicon chirped photonic crystals

Postprint (author's final draft

Distribution and Socio-spatial Segregation of cruise ship workers in Cozumel, Mexico

The cruise industry is one of the most profitable businesses in the world having a constant growth since the 1980’s. However, it is important to mention that this success has been reached in part due to the workforce in the vessels, better known as cruise ship crew members.As well as any other type of tourism, visitors have several effects on ports of call when vessels berth in ports of call. But even when there is knowledge on the effects of cruise tourism in the destinations (mainly caused by tourists), there is a scarcity of literature in terms of issues related to the cruise ship staff on land.In addition to the above, information about the activities and behaviour of the cruise workers, the knowledge of their specific distribution and socio-spatial segregation according to their hierarchies and nationalities during their free time in ports of call is practically null.Therefore, the aim of this research work is to point out the distribution of cruise ship workers in order to demonstrate their segregation in the Island of Cozumel, Mexico, according to the nation they come from and their position at work.Findings demonstrate that there are 79 different sites visited by crew members in Cozumel Island. It has also been identified that their distribution and socio-spatial segregation on the island is related to their hierarchies at work and nationalities, which could lead to a remarkable socioeconomic influence during their free time in the destination.

Propuesta para el desarrollo de una nueva estrategia comercial de tiempo compartido en Multivacaciones Decamerón dentro de la ciudad de Bogotá D.C

Administrador (a) de EmpresasPregrad

Size and emission wavelength control of InAs/InP quantum wires

For a certain heteroepitaxial system, the optical properties of self-assembled nanostructures basically depend on their size. In this work, we have studied different ways to modify the height of InAs/InP quantum wires (QWrs) in order to change the photoluminescence emission wavelength. One procedure consists of changing the QWr size by varying the amount of InAs deposited. The other two methods explored rely on the control of As/P exchange process, in one case during growth of InAs on InP for QWr formation and in the other case during growth of InP on InAs for QWr capping. The combination of the three approaches provides a fine tuning of QWr emission wavelength between 1.2 and 1.9 μm at room [email protected]

Sample collection/stabilization and DNA/RNA extraction from swab samples for microbiome or metagenome analyses

Good preservation and storage are essential to preserving microorganisms’ genetic material in microbial

Subspace Gaussian Mixture Models for Language Identification and Dysarthric Speech Intelligibility Assessment

En esta Tesis se ha investigado la aplicación de técnicas de modelado de subespacios de mezclas de Gaussianas en dos problemas relacionados con las tecnologías del habla, como son la identificación automática de idioma (LID, por sus siglas en inglés) y la evaluación automática de inteligibilidad en el habla de personas con disartria. Una de las técnicas más importantes estudiadas es el análisis factorial conjunto (JFA, por sus siglas en inglés). JFA es, en esencia, un modelo de mezclas de Gaussianas en el que la media de cada componente se expresa como una suma de factores de dimensión reducida, y donde cada factor representa una contribución diferente a la señal de audio. Esta factorización nos permite compensar nuestros modelos frente a contribuciones indeseadas presentes en la señal, como la información de canal. JFA se ha investigado como clasficador y como extractor de parámetros. En esta última aproximación se modela un solo factor que representa todas las contribuciones presentes en la señal. Los puntos en este subespacio se denominan i-Vectors. Así, un i-Vector es un vector de baja dimensión que representa una grabación de audio. Los i-Vectors han resultado ser muy útiles como vector de características para representar señales en diferentes problemas relacionados con el aprendizaje de máquinas. En relación al problema de LID, se han investigado dos sistemas diferentes de acuerdo al tipo de información extraída de la señal. En el primero, la señal se parametriza en vectores acústicos con información espectral a corto plazo. En este caso, observamos mejoras de hasta un 50% con el sistema basado en i-Vectors respecto al sistema que utilizaba JFA como clasificador. Se comprobó que el subespacio de canal del modelo JFA también contenía información del idioma, mientras que con los i-Vectors no se descarta ningún tipo de información, y además, son útiles para mitigar diferencias entre los datos de entrenamiento y de evaluación. En la fase de clasificación, los i-Vectors de cada idioma se modelaron con una distribución Gaussiana en la que la matriz de covarianza era común para todos. Este método es simple y rápido, y no requiere de ningún post-procesado de los i-Vectors. En el segundo sistema, se introdujo el uso de información prosódica y formántica en un sistema de LID basado en i-Vectors. La precisión de éste estaba por debajo de la del sistema acústico. Sin embargo, los dos sistemas son complementarios, y se obtuvo hasta un 20% de mejora con la fusión de los dos respecto al sistema acústico solo. Tras los buenos resultados obtenidos para LID, y dado que, teóricamente, los i-Vectors capturan toda la información presente en la señal, decidimos usarlos para la evaluar de manera automática la inteligibilidad en el habla de personas con disartria. Los logopedas están muy interesados en esta tecnología porque permitiría evaluar a sus pacientes de una manera objetiva y consistente. En este caso, los i-Vectors se obtuvieron a partir de información espectral a corto plazo de la señal, y la inteligibilidad se calculó a partir de los i-Vectors obtenidos para un conjunto de palabras dichas por el locutor evaluado. Comprobamos que los resultados eran mucho mejores si en el entrenamiento del sistema se incorporaban datos de la persona que iba a ser evaluada. No obstante, esta limitación podría aliviarse utilizando una mayor cantidad de datos para entrenar el sistema.In this Thesis, we investigated how to effciently apply subspace Gaussian mixture modeling techniques onto two speech technology problems, namely automatic spoken language identification (LID) and automatic intelligibility assessment of dysarthric speech. One of the most important of such techniques in this Thesis was joint factor analysis (JFA). JFA is essentially a Gaussian mixture model where the mean of the components is expressed as a sum of low-dimension factors that represent different contributions to the speech signal. This factorization makes it possible to compensate for undesired sources of variability, like the channel. JFA was investigated as final classiffer and as feature extractor. In the latter approach, a single subspace including all sources of variability is trained, and points in this subspace are known as i-Vectors. Thus, one i-Vector is defined as a low-dimension representation of a single utterance, and they are a very powerful feature for different machine learning problems. We have investigated two different LID systems according to the type of features extracted from speech. First, we extracted acoustic features representing short-time spectral information. In this case, we observed relative improvements with i-Vectors with respect to JFA of up to 50%. We realized that the channel subspace in a JFA model also contains language information whereas i-Vectors do not discard any language information, and moreover, they help to reduce mismatches between training and testing data. For classification, we modeled the i-Vectors of each language with a Gaussian distribution with covariance matrix shared among languages. This method is simple and fast, and it worked well without any post-processing. Second, we introduced the use of prosodic and formant information with the i-Vectors system. The performance was below the acoustic system but both were found to be complementary and we obtained up to a 20% relative improvement with the fusion with respect to the acoustic system alone. Given the success in LID and the fact that i-Vectors capture all the information that is present in the data, we decided to use i-Vectors for other tasks, specifically, the assessment of speech intelligibility in speakers with different types of dysarthria. Speech therapists are very interested in this technology because it would allow them to objectively and consistently rate the intelligibility of their patients. In this case, the input features were extracted from short-term spectral information, and the intelligibility was assessed from the i-Vectors calculated from a set of words uttered by the tested speaker. We found that the performance was clearly much better if we had available data for training of the person that would use the application. We think that this limitation could be relaxed if we had larger databases for training. However, the recording process is not easy for people with disabilities, and it is difficult to obtain large datasets of dysarthric speakers open to the research community. Finally, the same system architecture for intelligibility assessment based on i-Vectors was used for predicting the accuracy that an automatic speech recognizer (ASR) system would obtain with dysarthric speakers. The only difference between both was the ground truth label set used for training. Predicting the performance response of an ASR system would increase the confidence of speech therapists in these systems and would diminish health related costs. The results were not as satisfactory as in the previous case, probably because an ASR is a complex system whose accuracy can be very difficult to be predicted only with acoustic information. Nonetheless, we think that we opened a door to an interesting research direction for the two problems