Ultrafast control over chiral sum-frequency generation

We introduce an ultrafast all-optical approach for efficient chiral recognition which relies on the interference between two low-order nonlinear processes which are ubiquitous in nonlinear optics: sum-frequency generation and third-harmonic generation. In contrast to traditional sum-frequency generation, our approach encodes the medium's handedness in the intensity of the emitted harmonic signal, rather than in its phase, and it enables full control over the enantiosensitive response. We show how, by sculpting the sub-optical-cycle oscillations of the driving laser field, we can force one molecular enantiomer to emit bright light while its mirror twin remains dark, thus reaching the ultimate efficiency limit of chiral sensitivity via low-order nonlinear light-matter interactions. Our work paves the way for ultrafast and highly efficient imaging and control of the chiral electronic clouds of chiral molecules using lasers with moderate intensities, in all states of matter: from gases to liquids to solids, with molecular specificity and on ultrafast timescales

Diversidad Genética y cambios demográficos históricos en la población del delfín Costero Sotalia guianensis (Cetacea: Delphinidae) de la desembocadura del Río Amazonas, en la ciudad de Belém, Brasil

Los delfines del género Sotalia se encuentran distribuidos por todas las costas del océano Atlántico en América Central y del Sur, así mismo como en el Río Amazonas y algunos de sus afluyentes. Actualmente se reconocen dos especies dentro de este género: Sotalia fluviatilis (Gervais, 1853) como la especie de río, y Sotalia guianensis (Van Bénéden, 1864) como la especie costera (Caballero et al., 2007). La historia evolutiva de esta especie de delfín es prácticamente desconocida. La genética de poblaciones, mediante el uso de marcadores moleculares, modelos y metodologías matemáticas, puede intentar reconstruir dicha historia y ofrecer herramientas efectivas para la aplicación de políticas correctas de conservación.Biólogo (a)Pregrad

On-line learning and anomaly detection methods : applications to fault assessment

[Abstract] This work lays at the intersection of two disciplines, Machine Learning (ML) research and predictive maintenance of machinery. On the one hand, Machine Learning aims at detecting patterns in data gathered from phenomena which can be very different in nature. On the other hand, predictive maintenance of industrial machinery is the discipline which, based on the measurement of physical conditions of its internal components, assesses its present and near future condition in order to prevent fatal failures. In this work it is highlighted that these two disciplines can benefit from their synergy. Predictive maintenance is a challenge for Machine Learning algorithms due to the nature of data generated by rotating machinery: (a) each machine constitutes an new individual case so fault data is not available for model construction and (b) working conditions of the machine are changeable in many situations and affects captured data. Machine Learning can help predictive maintenance to: (a) cut plant costs though the automation of tedious periodic tasks which are carried out by experts and (b) reduce the probability of fatal damages in machinery due to the possibility of monitoring it more frequently at a modest cost increase. General purpose ML techniques able to deal with the aforementioned conditions are proposed. Also, its application to the specific field of predictive maintenance of rotating machinery based on vibration signature analysis is thoroughly treated. Since only normal state data is available to model the vibration captures of a machine, we are restricted to the use of anomaly detection algorithms, which will be one of the main blocks of this work. In addition, predictive maintenance also aims at assessing its state in the near future. The second main block of this work, on-line learning algorithms, will help us in this task. A novel on-line learning algorithm for a single layer neural network with a non-linear output function is proposed. In addition to the application to predictive maintenance, the proposed algorithm is able to continuously train a network in a one pattern at a time manner. If some conditions are hold, it analytically ensures to reach a global optimal model. As well as predictive maintenance, the proposed on-line learning algorithm can be applied to scenarios of stream data learning such as big data sets, changing contexts and distributed data. Some of the principles described in this work were introduced in a commercial software prototype, GIDASR ? . This software was developed and installed in real plants as part of the work of this thesis. The experiences in applying ML to fault detection with this software are also described and prove that the proposed methodology can be very effective. Fault detection experiments with simulated and real vibration data are also carried out and demonstrate the performance of the proposed techniques when applied to the problem of predictive maintenance of rotating machinery.[Resumen] La presente tesis doctoral se sitúa en el ámbito de dos disciplinas, la investigación en Aprendizaje Computacional (AC) y el Mantenimiento Predictivo (MP) de maquinaria rotativa. Por una parte, el AC estudia la problemática de detectar y clasificar patrones en conjuntos de datos extraídos de fenómenos de interés de la más variada naturaleza. Por su parte, el MP es la disciplina que, basándose en la monitorización de variables físicas de los componentes internos de maquinaria industrial, se encarga de valorar las condiciones de éstos tanto en el momento presente como en un futuro próximo con el fin último de prevenir roturas que pueden resultar de fatales consecuencias. En este trabajo se pone de relevancia que ambas disciplinas pueden beneficiarse de su sinergia. El MP supone un reto para el AC debido a la naturaleza de los datos generados por la maquinaria: (a) las propiedades de las medidas físicas recogidas varían para cada máquina y, debido a que la monitorización debe comenzar en condiciones correctas, no contamos con datos de fallos para construir un modelo de comportamiento y (b) las condiciones de funcionamiento de las máquinas pueden ser variables y afectar a los datos generados por éstas. El AC puede ayudar al MP a: (a) reducir costes a través de la automatización de tareas periódicas tediosas que tienen que ser realizadas por expertos en el área y (b) reducir la probabilidad de grandes da˜nos a la maquinaria gracias a la posibilidad de monitorizarla con una mayor frecuencia sin elevar los costes sustancialmente. En este trabajo, se proponen algoritmos de AC de propósito general capaces de trabajar en las condiciones anteriores. Además, su aplicación específica al campo del mantenimiento predictivo de maquinaria rotativa basada en el análisis de vibraciones se estudia en detalle, aportando resultados para casos reales. El hecho de disponer sólamente de datos en condiciones de normalidad de la maquinaria nos restringe al uso de técnicas de detección de anomalías. éste será uno de los bloques principales del presente trabajo. Por otra parte, el MP también intenta valorar si la maquinaria se encontrará en un estado inaceptable en un futuro próximo. En el segundo bloque se presenta un nuevo algoritmo de aprendizaje en tiempo real (on-line) que será de gran ayuda en esta tarea. Se propone un nuevo algoritmo de aprendizaje on-line para una red neuronas monocapa con función de transferencia no lineal. Además de su aplicación al mantenimiento predictivo, el algoritmo propuesto puede ser empleado en otros escenarios de aprendizaje on-line como grandes conjuntos de datos, cambios de contexto o datos distribuidos. Algunas de las ideas descritas en este trabajo fueron implantadas en un prototipo de software comercial, GIDASR ? . Este software fue desarrollado e implantado en plantas reales por el autor de este trabajo y las experiencias extraídas de su aplicación también se describen en el presente volumen[Resumo] O presente traballo sitúase no ámbito de dúas disciplinas, a investigación en Aprendizaxe Computacional (AC) e o Mantemento Predictivo (MP) de maquinaria rotativa. Por unha banda, o AC estuda a problemática de detectar e clasificar patróns en conxuntos de datos extraídos de fenómenos de interese da máis variada natureza. Pola súa banda, o MP é a disciplina que, baseándose na monitorización de variables físicas dos seus compo˜nentes internos, encárgase de valorar as condicións destes tanto no momento presente como nun futuro próximo co fin último de previr roturas que poden resultar de fatais consecuencias. Neste traballo ponse de relevancia que ambas disciplinas poden beneficiarse da súa sinergia. O MP supón un reto para o AC debido á natureza dos datos xerados pola maquinaria: (a) as propiedades das medidas físicas recolleitas varían para cada máquina e, debido a que a monitorización debe comezar en condicións correctas, non contamos con datos de fallos para construír un modelo de comportamento e (b) as condicións de funcionamento das máquinas poden ser variables e afectar aos datos xerados por estas. O AC pode axudar ao MP a: (a) reducir custos a través da automatización de tarefas periódicas tediosas que te˜nen que ser realizadas por expertos no área e (b) reducir a probabilidade de grandes danos na maquinaria grazas á posibilidade de monitorizala cunha maior frecuencia sen elevar os custos sustancialmente. Neste traballo, propó˜nense algoritmos de AC de propósito xeral capaces de traballar nas condicións anteriores. Ademais, a súa aplicación específica ao campo do mantemento predictivo de maquinaria rotativa baseada na análise de vibracións estúdase en detalle aportando resultados para casos reais. Debido a contar só con datos en condicións de normalidade da maquinaria, estamos restrinxidos ao uso de técnicas de detección de anomalías. éste será un dos bloques principais do presente traballo. Por outra banda, o MP tamén intenta valorar si a maquinaria atoparase nun estado inaceptable nun futuro próximo. No segundo bloque do presente traballo preséntase un novo algoritmo de aprendizaxe en tempo real (on-line) que será de gran axuda nesta tarefa. Proponse un novo algoritmo de aprendizaxe on-line para unha rede neuronas monocapa con función de transferencia non lineal. Ademais da súa aplicación ao mantemento predictivo, o algoritmo proposto pode ser empregado en escenarios de aprendizaxe on-line como grandes conxuntos de datos, cambios de contexto ou datos distribuídos. Algunhas das ideas descritas neste traballo foron implantadas nun prototipo de software comercial, GIDASR ? . Este software foi desenvolvido e implantado en plantas reais polo autor deste traballo e as experiencias extraídas da súa aplicación tamén se describen no presente volume

Experiencia de adaptación y plan de mejora de la materia de Sistemas Inteligentes en la titulación de Grado en Ingeniería Informática

En este trabajo se exponen las experiencias asociadas a la adaptación al Espacio Europeo de Educación Superior para la asignatura de Sistemas Inteligentes en la titulación de Grado en Ingeniería Informática de la Universidade da Coruña. Al respecto, se comentará el proyecto de guía docente que ha sido elaborado para la materia, así como también los problemas más importantes que se han detectado, y algunos de los resultados de las evaluaciones de alumnos que se han obtenido tras el primer año de implantación, y que utilizaremos para plantear alternativas que permitan mejorar esos resultados. Con respecto a los problemas encontrados se detallarán en primer lugar, los inconvenientes ocasionados debido a la ubicación de la materia dentro del nuevo plan de estudios y en segundo lugar, los problemas generados por la organización, el calendario y la metodología docente seguida. Finalmente se comentan las posibilidades de mejora y el trabajo desarrollado para implantar un plan de seguimiento que permita subsanar, en la medida de nuestras posibilidades, los principales inconvenientes detectados.SUMMARY -- This paper describes the experiences obtained from adapting the Intelligent Systems subject of the Degree in Computer Engineering of the University of A Coruña to the European Higher Education Area (EHEA). First, the teaching guide of the subject is detailed, and later the problems that the teachers have faced in applying it. Finally, some of the student’s evaluation results obtained during the process are analyzed and used to propose possible improvements in future courses. Regarding the main problems we will describe, firstly, the structural issues caused by the subject’s placement in the new curriculum and, secondly, some difficulties related to organization, scheduling, and teaching methodology. Several possible solutions to the encountered problems are analyzed, together with a plan to implement them, with the aim of correcting the problems detected

Biofeedback Augmented Gameplay: Criação de Uma Framework para o Desenvolvimento de Mecanismos de Interacção Fisiológica em Videojogos Comerciais

Desde que os videojogos foram criados, o modo como o utilizador interage com o mesmo praticamente não mudou. Os controladores tradicionais (teclado/rato) criam uma barreira fisica e emocional entre o videojogo e o utilizador, e com isso, originam uma experiência de jogo pouco imersiva e ativa. No entanto, nos últimos anos houve um crescente interesse em criar novos mecanismos na procura de alargar a forma como jogamos os videojogos, tais como os mecanismos de interação natural. Mesmo que estes novos mecanismos tragam novas experiências aos utilizadores, não resolvem o paradigma da barreira física e emocional, porque ignoram conceitos tais como a emoção do utilizador, entre outros. Com o objetivo de corrigir estas falhas e tornar o utilizador uma parte integrante do videojogo, foi concebido este projeto, que visa criar uma framework que implemente mecanismos de biofeedback. Esta framework tem o objetivo de receber, tratar e mapear os dados fisiológicos do utilizador nos controladores de jogo, de forma a criar uma experiência de jogo imersiva.Since the video games were created, the way the user interacts with it hardly changed. The traditional controllers ( keyboard / mouse ) create a physical and emotional barrier between the videogame and the user , and thus , yield a less active and immersive gaming experience. However, in recent years there has been a growing interest in creating new mechanisms in seeking to extend the way we play video games, such as the natural interaction mechanisms.Even though these new mechanisms bring new experiences to users, they do not solve the paradigm of the physical and emotional barrier, because they ignore concepts such as the emotion of the user, among others . In order to fix these issues and make the user an integral part of the video game this project was designed, and aims to create a framework that implements mechanisms of biofeedback. This framework is designed to receive, process and map the physiological data from the user in game controllers, in order to create an immersive gaming experience

Jacobian Ensembles Improve Robustness Trade-offs to Adversarial Attacks

Deep neural networks have become an integral part of our software infrastructure and are being deployed in many widely-used and safety-critical applications. However, their integration into many systems also brings with it the vulnerability to test time attacks in the form of Universal Adversarial Perturbations (UAPs). UAPs are a class of perturbations that when applied to any input causes model misclassification. Although there is an ongoing effort to defend models against these adversarial attacks, it is often difficult to reconcile the trade-offs in model accuracy and robustness to adversarial attacks. Jacobian regularization has been shown to improve the robustness of models against UAPs, whilst model ensembles have been widely adopted to improve both predictive performance and model robustness. In this work, we propose a novel approach, Jacobian Ensembles-a combination of Jacobian regularization and model ensembles to significantly increase the robustness against UAPs whilst maintaining or improving model accuracy. Our results show that Jacobian Ensembles achieves previously unseen levels of accuracy and robustness, greatly improving over previous methods that tend to skew towards only either accuracy or robustness

Collateral Optimization : Liquidity & Funding Value Adjustments, - Best Practices -

The purpose of this paper is to understand how the current financial landscape shaped by the crises and new regulations impacts Investment Banking’s business model. We will focus on quantitative implications, i.e. valuation, modeling and pricing issues, as well as qualitative implications, i.e. best practices to manage quantitative aspects and handle these functions to the current Investment Banking organization. We considered two pillars to shape our vision of collateral optimization: 1. Collateral as a refinancing instrument. Collateral is shifting from a mere hedging instrument for counterparty risk to a strategic refinancing instrument. 2. Improve asymmetric collateral quality and profitability. Recent requirements on collateralization highly impact collateral management through the increase in haircuts and funding of good-quality collateral. As a result, more and more banks are considering their net collateral balance as a KPI, i.e. monitoring their net collateral balance position and identifying the need in cash funding or transforming. We built our approach on three key standards: • In most cases, banks should prioritize the reception of cash and delivery of securities, what we call “Asymmetric Collateral Management”. - This implies banks have to capitalize on their valuation functions to boost profitability of the net collateral balance and take advantage of pricing conditions (e.g. for CSA Discounting, precise valuation and pricing of LVA/FVA). • Regarding Management of Non-Cash Collateral, banks should focus on - Optimization of the cash-circuit to manage the various levers of Non-Cash Collateral Transformation into Cash (repo market, central bank loans, re-hypothecation of received non-cash collateral as collateral for other deals). - Management of the collateral quality (both received and delivered), to source and receive high quality collateral and deliver lower quality collateral (Cheapest-To-Deliver Collateral Management). • Considering Management of Liquidity Issues, banks should carefully consider Collateral Management in case of liquidity issues (e.g. sale in case of default, use of re-hypothecation). Being unable to deliver good quality collateral can be seen as a negative sign for the counterparty’s financial health. We will further study the Collateral Offer Services of top financial institutions, providing specific expertise and a tailor-made approach to the new challenges of Collateral Management

The art nouveau landscape of the villas of Cartagena countryside

[SPA] La ciudad de Cartagena (Murcia) comenzó la segunda mitad del siglo XIX alcanzando un pronunciado desarrollo económico que se dejó sentir de forma clara en la sociedad, donde pronto surgió una potente burguesía que, culta e interesada por el arte, recurrió a la nueva arquitectura como medio para reafirmar su distinción social y hacer ostentación de su riqueza. De este modo, durante las primeras décadas del siglo XX la ciudad portuaria fue objeto de una profunda transformación arquitectónica siguiendo el gusto modernista imperante en dicho momento, caracterizado por el gran desarrollo de las artes decorativas, que encontraron fundamentalmente en los motivos exóticos y la naturaleza sus principales fuentes de inspiración. En este sentido, la temática vegetal modernista se ha apuntado tradicionalmente en dos direcciones: la que atiende a la exterioridad (la fachada, la ciudad) y la que apunta a la intimidad (el interior, la vivienda). Lo que se abordará en esta comunicación es la justificación de la existencia de un tercer enfoque de carácter más natural en el que la propia vegetación se convierte en componente principal junto con la colaboración de ciertos componentes arquitectónicos. Nos referimos a la jardinería ligada a las imponentes villas construidas por el burgués en el Campo de Cartagena con el objeto de disponer de un lugar donde alejarse de la ciudad, destinado tanto para el reposo, ocio y relación social, como para disfrutar de las vistas y el ambiente saludable y fresco de su entorno natural. [ENG] The city of Cartagena (Murcia) began the second half of the 19th century with a high economic growth that produced a major transformation of the society. Thus creating the emergence of, a powerful bourgeoisie, being cultured and interested in art, decided to use the new architecture as a means to reassert its social distinction and to flaunt their wealth. As a consequence of this, at the beginning of the 20th century the port city suffered a profound architectural transformation following the art nouveau present at the time. This new artistic movement was characterized by a great development of the decorative arts, which found in exotic motives and nature its main sources of inspiration. In this sense, the art nouveau plant theme has been traditionally targeted in two directions: serving the outward appearance (the facade, the city) and pointing to privacy (the inside, the home). In this report, the justification of the existence of a third approach with a more natural character in which the vegetation becomes the main component together with the collaboration of some architectural components, will be addressed. We refer to the gardening linked to the great villas built in the Cartagena countryside by the bourgeoisie in order to have a place away from the city, intended for, both to rest, leisure and social relationships, and to enjoy the view and healthy and fresh atmosphere of its natural environment

La biblioteca sale al encuentro del usuario. Bibliopraza de O Porriño (Pontevedra)

[ES] Se describe el funcionamiento de la Bibliopraza de O Porriño (Pontevedra). Se trata de un servicio de ex- tensión bibliotecaria al aire libre, por lo que se lleva a cabo en los meses de mayo y junio. Todo en este servicio gira en torno a su provisionalidad y flexibilidad: los destinatarios, el tipo de instalación, el mobiliario, la colección y las actividades de animación a la lectura

Transversal competences and employability of university students: converging towards service-learning

We are living in times of great transformations within the field of education and the labor market. These changes are connected and have to do with an expanded knowledge society, whose implications reach the levels of employability in times of uncertainty. Within this framework, the main purpose of our study is to perform a theoretical analysis and an empirical approach to the influence that transversal competences (soft skills) may have on the degree of employability of university students. We have identified some of those competences and we have tested them with a sample of 83 employers and 1249 students using a Likert scale. Our results show the interest of employers in the mastery of transversal competences and inequalities in terms of students’ perception thereof. We did not find any significant differences between students starting their degree and those who were about to complete it. However, we did find differences between the students who participated in experiential activities and those who did not, in favor of the former. Due to the importance of experiential learning in our results, we dedicate our discussion to theoretically exploring whether the pedagogical approach of Service-Learning (SL) might contribute to a better connection between transversal competences and employabilityS