Is the leadership of the Brent-WTI threatened by China's new crude oil futures market?

The recent listing of a new crude oil futures contract on the Shanghai International Energy Exchange (INE) has reopened the debate over whether crude oil produced in different countries or locations constitutes a unified world oil market. The aim of this paper is to study the information flows among Brent, West Texas Intermediate (WTI) and the new Medium Sour Crude Oil (SC) futures contract listed on INE futures markets to assess whether the trading of this new futures contract has altered the dominant role of the most traded oil benchmarks in the world. A multiple regression model identifies the Brent futures market as the most influential market in the oil price discovery process, while WTI appears to be the most sensitive. Furthermore, we have observed that SC does not influence any market and it is only sensitive to Brent news, even though WTI is the most heavily traded futures contract. Therefore, the launch of the SC futures contract has not yet altered the dominant role of Brent over WTI

Técnicas de fotogrametría y tratamiento de imágenes para a monitorización de playas

[EN] The land-water boundary varies according to the sea level and the shape of a beach profile that is continuously modelled by incident waves. Attempting to model the response of a landscape as geomorphologically volatile as beaches requires multiple precise measurements to recognize responses to the actions of various geomorphic agents. It is therefore essential to have monitoring systems capable of systematically recording the shoreline accurately and effectively. New methods and tools are required to efficiently capture, characterize, and analyze information – and so obtain geomorphologically significant indicators. This is the aim of the doctoral thesis, focusing on the development of tools and procedures for coastal monitoring using satellite images and terrestrial photographs. The work brings satellite image processing and photogrammetric solutions to scientists, engineers, and coastal managers by providing results that demonstrate the usefulness of these viable and lowcost techniques. Existing and freely accessible public information (satellite images, video-derived data, or crowdsourced photographs) can be converted into high quality data for monitoring morphological changes on beaches and thus help achieve a sustainable management of coastal resources.[ES] El límite tierra-agua varía en función de la posición del nivel del mar y de la forma del perfil de playa que continuamente queda modelado por las olas incidentes. Intentar modelizar la respuesta de un paisaje tan voluble geomorfológicamente como las playas requiere disponer de múltiples medidas registradas con suficiente precisión para poder reconocer su respuesta frente a la acción de los distintos agentes geomórficos. Para ello resulta esencial disponer de diferentes sistemas de monitorización capaces de registrar de forma sistemática la línea de costa con exactitud y efectividad. Se requieren nuevos métodos y herramientas informáticas que permitan capturar, caracterizar y analizar eficientemente la información con el objeto de obtener indicadores con significación geomorfológica de calidad. En esto radica el objetivo de la presente tesis doctoral, centrándose en el desarrollo de herramientas y procedimientos eficientes para la monitorización costera mediante el uso de imágenes satelitales y fotografías terrestres. El trabajo aporta soluciones de procesamiento de imágenes de satélite y fotogramétricas a científicos, ingenieros y gestores costeros, proporcionando resultados que evidencian la gran utilidad de estas técnicas viables y de bajo coste para la monitorización costera. Mediante ellas se puede convertir información pública existente y de libre acceso (imágenes satelitales, datos de video cámaras o fotografías de la ciudadanía) en datos de alta calidad para el monitoreo de los cambios morfológicos de las playas, y lograr así una consiguiente gestión sostenible de los recursos costeros.This study was supported by the grant of E. Sánchez-García (FPU13/ 05877) from the Spanish Ministry of Education, Culture and Sports, as well as the project RESETOCOAST (CGL 2015-69906-R) from the Spanish Ministry of Economy and Competitiveness.Sánchez-García, E.; Balaguer-Beser, Á.; Pardo-Pascual, JE. (2020). Photogrammetry and image processing techniques for beach monitoring. https://doi.org/10.4995/raet.2020.14107OJ

C-Pro: A coastal projector monitoring system using terrestrial photogrammetry with a geometric horizon constraint

[EN] This paper describes a methodological protocol to project a terrestrial photograph of a coastal area or whatever indicator is contained on it in a georeferenced plane taking advantage of the terrestrial horizon as a geometric key. This feature, which appears in many beach photos, helps in camera repositioning and as a constraint in collinearity adjustment. This procedure is implemented in a tool called Coastal Projector (C-Pro) that is based on Matlab and adapts its methodology in accordance with the input data and the available parameters of the acquisition system. The method is tested in three coastal areas to assess the influence that the horizon constraint presents in the results. The proposed methodology increases the reliability and efficient use of existing recreational cameras (with non-optimal requirements, unknown image calibration, and at elevations lower than 7 m) to provide quantitative coastal data.This study is part of the PhD dissertation of the first author, which is supported by a grant from the Spanish Ministry of Education, Culture and Sports (I+D+i 2013–2016). Two other projects participated: one from the Spanish Ministry of Economy and Competitiveness (CGL2015-69906-R) and the other from the Valencia Regional Government (AICO/2015/098). The Department of Geology, Faculty of Science of the University of Lisbon provided Magoito data thanks to a PhD stay of the first author under the supervision of Dr. Rui Taborda. The authors gratefully acknowledge the constructive comments provided by Dr. Jaime Almonacid.Sánchez García, E.; Balaguer-Beser, Á.; Pardo Pascual, JE. (2017). C-Pro: A coastal projector monitoring system using terrestrial photogrammetry with a geometric horizon constraint. ISPRS Journal of Photogrammetry and Remote Sensing. 128:255-273. https://doi.org/10.1016/j.isprsjprs.2017.03.023S25527312

Carbon and safe-haven flows

This paper explores the role of European Union Allowances (EUAs) as a safe haven for a range of assets and analyses the effect of safe-haven flows on the European carbon futures market. In particular, we demonstrate that EUAs can be considered a refuge against fluctuations in corporate bonds, gold and volatility-related assets in periods of market turmoil. Furthermore, we have shown that extremely bearish and bullish movements in those assets for which the EUA acts as a safe haven induce excess volatility in carbon markets, higher carbon trading volume and larger than normal EUA bid-ask spreads. These findings support the idea that some traders, by considering carbon futures as a refuge asset, induce safe-haven flows into the carbon market. The presence of these flows provides additional insights into the financialisation of the European carbon futures market

Identificación de impactos sobre flora rara, endémica o amenazada mediante el análisis de secuencias espaciotemporales

En el presente trabajo se muestran los resultados obtenidos a partir de una metodología de seguimiento de poblaciones de flora rara, endémica o amenazada –concretamente la cistácea Helianthemum caput-felis Boiss. en el litoral sur de la provincia de Alicante- con el fin de constatar extinciones recientes de estas especies mediante la utilización combinada de Sistemas de Información Geográfica (SIG), Sistemas de Posicionamiento Global (GPS) y la aplicación Google Earth. Finalmente se reflexiona, a partir de la experiencia de trabajo con la especie referida, sobre las ventajas que puede significar esta última aplicación a la hora de difundir los datos y facilitar así la gestión y conservación de la flora y sus hábitats

Olfactory fMRI Connectivity Analysis Based on Granger Causality with Application in Anosmia Assessment

In this work, we describe hubs organization within the olfactory network with Functional Magnetic Resonance Imaging (fMRI). Granger causality analyses were applied in the supposed regions of interest (ROIs) involved in olfactory tasks, as described in [1]. We aim to get deeper knowledge about the hierarchy of the regions within the olfactory network and to describe which of these regions, in terms of strength of the connectivity, impair in different types of anosmia

Do neighboring municipalities matter in industrial location decisions? Empirical evidence from Spain

This paper focuses on industrial location, assuming that entrepreneurs not only consider the advantages associated with a certain municipality, but also those coming from nearby areas. Exploratory analysis reflects the existence of spatial patterns in the creation of manufacturing establishments and sheds light on the geographical scope on which agglomeration economies operate in industrial location. Spatial Probit models and standard Probit models with spatially lagged explanatory variables are estimated to test whether neighboring municipalities’ location decisions and characteristics, including agglomeration economies, matter in industrial location choices. Results show that neighboring municipalities location decisions and characteristics help to explain location decisions of new establishments for 11 manufacturing industries in Spanish municipalities (NUTS V) over the period 1991–1995

Bridge damage identification under varying environmental and operational conditions combining Deep Learning and numerical simulations

This work proposes a novel supervised learning approach to identify damage in operating bridge structures. We propose a method to introduce the effect of environmental and operational conditions into the synthetic damage scenarios employed for training a Deep Neural Network, which is applicable to large-scale complex structures. We apply a clustering technique based on Gaussian Mixtures to effectively select Q representative measurements from a long-term monitoring dataset. We employ these measurements as the target response to solve various Finite Element Model Updating problems before generating different damage scenarios. The synthetic and experimental measurements feed two Deep Neural Networks that assess the structural health condition in terms of damage severity and location. We demonstrate the applicability of the proposed method with a real full-scale case study: the Infante Dom Henrique bridge in Porto. A comparative study reveals that neglecting different environmental and operational conditions during training detracts the damage identification task. By contrast, our method provides successful results during a synthetic validation

Morphology and optical properties of ordered GaN and InGaN nanocolumns grown on non-polar and semipolar orientations

Relacionado con línea de investigación del GDS del ISO

Deep learning enhanced principal component analysis for structural health monitoring

This paper proposes a Deep Learning Enhanced Principal Component Analysis (PCA) approach for outlier detection to assess the structural condition of bridges. We employ partially explainable autoencoder architecture to replicate and enhance the data compression and reconstruction ability of PCA. The particularity of the method lies in the addition of residual connections to account for nonlinearities. We apply the proposed method to monitoring data obtained from two bridges under real operation conditions and compare the results before and after adding the residual connections. Results show that the addition of residual connections enhances the outlier detection ability of the network, allowing to detect lighter damages