Influence of general convective motions on the exterior of isolated rotating bodies in equilibrium

The problem of describing isolated rotating bodies in equilibrium in General Relativity has so far been treated under the assumption of the circularity condition in the interior of the body. For a fluid without energy flux, this condition implies that the fluid flow moves only along the angular direction, i.e. there is no convection. Using this simplification, some recent studies have provided us with uniqueness and existence results for asymptotically flat vacuum exterior fields given the interior sources. Here, the generalisation of the problem to include general sources is studied. It is proven that the convective motions have no direct influence on the exterior field, and hence, that the aforementioned results on uniqueness and existence of exterior fields apply equally in the general case.Comment: 8 pages, LaTex, uses iopart style files. To appear in Class. Quatum Gra

Stationary axisymmetric exteriors for perturbations of isolated bodies in general relativity, to second order

Perturbed stationary axisymmetric isolated bodies, e.g. stars, represented by a matter-filled interior and an asymptotically flat vacuum exterior joined at a surface where the Darmois matching conditions are satisfied, are considered. The initial state is assumed to be static. The perturbations of the matching conditions are derived and used as boundary conditions for the perturbed Ernst equations in the exterior region. The perturbations are calculated to second order. The boundary conditions are overdetermined: necessary and sufficient conditions for their compatibility are derived. The special case of perturbations of spherical bodies is given in detail.Comment: RevTeX; 32 pp. Accepted by Phys. Rev. D. Added references and extra comments in introductio

On global models for isolated rotating axisymmetric charged bodies; uniqueness of the exterior field

A relatively recent study by Mars and Senovilla provided us with a uniqueness result for the exterior vacuum gravitational field generated by an isolated distribution of matter in axial rotation in equilibrium in General Relativity. The generalisation to exterior electrovacuum gravitational fields, to include charged rotating objects, is presented here.Comment: LaTeX, 21 pages, uses iopart styl

Structuring Climate Service Co-Creation Using a Business Model Approach

[EN] Climate services are tools or products that aim to support climate-informed decision making for the adaptation to climate change. The market for climate services is dominated by public institutions, despite the efforts made by the European Commission to increase private enterprise in the market. The business model perspective has been proposed as a framework for enabling market growth through the development of appropriate business models for the provision of climate services. However, there is a lack of structured knowledge on how to approach climate service design and development from a business model standpoint. In this contribution, we first analyze the role of stakeholders in the design and development of climate services and identify opportunities for engaging users in the creation process. Afterwards, we explain our approach to climate service design and development using a business model perspective. To illustrate the proposed approach, we describe the co-creation of a climate service to support the adaptation to climate change of the urban water supply system in Valencia, Spain, and discuss the main findings and lessons learned from applying this approach.We acknowledge the European Research Area for Climate Services consortium (ER4CS) and the Agencia Estatal de Investigacion for their financial support to this research under the INNOVA project (Grant Agreement: 690462; PCIN-2017-066). This study has also been partially funded by the ADAPTAMED project (RTI2018-101483-B-I00) from the Ministerio de Ciencia, Innovacion y Universidades (MICIU) of Spain.Rubio-Martín, A.; Máñez-Costa, M.; Pulido-Velazquez, M.; Garcia-Prats, A.; Celliers, L.; Llario, F.; Macián Cervera, VJ. (2021). Structuring Climate Service Co-Creation Using a Business Model Approach. Earth's Future. 9(10):1-18. https://doi.org/10.1029/2021EF002181S11891

Symmetry-preserving matchings

In the literature, the matchings between spacetimes have been most of the times implicitly assumed to preserve some of the symmetries of the problem involved. But no definition for this kind of matching was given until recently. Loosely speaking, the matching hypersurface is restricted to be tangent to the orbits of a desired local group of symmetries admitted at both sides of the matching and thus admitted by the whole matched spacetime. This general definition is shown to lead to conditions on the properties of the preserved groups. First, the algebraic type of the preserved group must be kept at both sides of the matching hypersurface. Secondly, the orthogonal transivity of two-dimensional conformal (in particular isometry) groups is shown to be preserved (in a way made precise below) on the matching hypersurface. This result has in particular direct implications on the studies of axially symmetric isolated bodies in equilibrium in General Relativity, by making up the first condition that determines the suitability of convective interiors to be matched to vacuum exteriors. The definition and most of the results presented in this paper do not depend on the dimension of the manifolds involved nor the signature of the metric, and their applicability to other situations and other higher dimensional theories is manifest.Comment: LaTeX, 19 page

Aspectes jurisdiccionals de l'administració d'un territori: el cas del Camp de Tarragona del 1477 fins al 1675

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Determining the optimal features in freezing of gait detection through a single waist accelerometer in home environments

Freezing of gait (FoG) is one of the most disturbing and incapacitating symptoms in Parkinson's disease. It is defined as a sudden block in effective stepping, provoking anxiety, stress and falls. FoG is usually evaluated by means of different questionnaires; however, this method has shown to be not reliable, since it is subjective due to its dependence on patients’ and caregivers’ judgment. Several authors have analyzed the usage of MEMS inertial systems to detect FoG with the aim of objectively evaluating it. So far, specific methods based on accelerometer's frequency response has been employed in many works; nonetheless, since they have been developed and tested in laboratory conditions, their performance is commonly poor when being used at patients’ home. Therefore, this work proposes a new set of features that aims to detect FoG in real environments by using accelerometers. This set of features is compared with three previously reported approaches to detect FoG. The different feature sets are trained by means of several machine learning classifiers; furthermore, different window sizes are also evaluated. In addition, a greedy subset selection process is performed to reduce the computational load of the method and to enable a real-time implementation. Results show that the proposed method detects FoG at patients’ home with 91.7% and 87.4% of sensitivity and specificity, respectively, enhancing the results of former methods between a 5% and 11% and providing a more balanced rate of true positives and true negatives.Peer ReviewedPostprint (published version

Sensitivity of two methods to detect Mycoplasma agalactiae in goat milk

© 2015 Tatay-Dualde et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background: Laboratory diagnostic techniques able to detect Mycoplasma agalactiae are essential in contagious agalactia in dairy goats. This study was designed: 1) to determine the detection limits of PCR and culture in goat milk samples, 2) to examine the effects of experimental conditions including the DNA extraction method, PCR technique and storage conditions (fresh versus frozen stored milk samples) on these methods and 3), to establish agreement between PCR and culture techniques using milk samples from goats with mastitis in commercial dairy herds. The study was conducted both on artificially inoculated and field samples. Results: Our findings indicate that culture is able to detect M. agalactiae in goat milk at lower concentrations than PCR. Qualitative detection of M.agalactiae by culture and PCR was not affected by sample freezing, though the DNA extraction method used significantly affected the results of the different PCR protocols. When clinical samples were used, both techniques showed good agreement. Conclusions: The results from this study indicate that both culture and PCR are able to detect M. agalactiae in clinical goat mastitis samples. However, in bulk tank milk samples with presumably lower M. agalactiae concentrations, culture is recommended within the first 24 h of sample collection due to its lower limit of detection. To improve the diagnostic sensitivity of PCR in milk samples, there is a need to increase the efficiency of extracting DNA from milk samples using protocols including a previous step of enzymatic digestion

Deep learning for detecting freezing of gait episodes in Parkinson’s disease based on accelerometers

The final publication is available at Springer via https://doi.org/10.1007/978-3-319-59147-6_30Freezing of gait (FOG) is one of the most incapacitating symptoms among the motor alterations of Parkinson’s disease (PD). Manifesting FOG episodes reduce patients’ quality of life and their autonomy to perform daily living activities, while it may provoke falls. Accurate ambulatory FOG assessment would enable non-pharmacologic support based on cues and would provide relevant information to neurologists on the disease evolution. This paper presents a method for FOG detection based on deep learning and signal processing techniques. This is, to the best of our knowledge, the first time that FOG detection is addressed with deep learning. The evaluation of the model has been done based on the data from 15 PD patients who manifested FOG. An inertial measurement unit placed at the left side of the waist recorded tri-axial accelerometer, gyroscope and magnetometer signals. Our approach achieved comparable results to the state-of-the-art, reaching validation performances of 88.6% and 78% for sensitivity and specificity respectively.Peer ReviewedPostprint (author's final draft

Mapeo de áreas regadas usando datos geoespaciales y teledetección en el municipio de Caudete de las Fuentes (Valencia)

Las políticas de control del uso agrícola de aguas subterráneas mediante la inspección de contadores se han demostrado caras y poco eficientes, mientras que en algunos estudios se ha obtenido resultados prometedores mediante la teledetección. El rápido progreso de las tecnologías de teledetección ha hecho posible su aplicación para la identificación de áreas regadas, y los nuevos sensores y técnicas de inteligencia artificial abren nuevas oportunidades a mejorar su eficacia y precisión. Nuestro trabajo propone una metodología de bajo coste y eficiente para detectar viña en riego a escala de parcela con el fin de mejorar la gestión colectiva de aguas subterráneas. A partir de información oficial se ha distinguido la superficie regada con técnicas de análisis de aprendizaje automático, empleando variables que condicionan el estado hídrico de la planta para la temporada de riego 2019. La metodología calcula la humedad del suelo con el método OPTRAM (OPtical TRApezoid Model) de análisis multitemporal de imágenes procedentes de plataformas satelitales. Estos datos son integrados en un SIG junto a información climática, topográfica e información propia del cultivo. Finalmente, en base a inventarios de verdad-terreno se aplica un clasificador de aprendizaje automático para estimar la superficie regada con agua procedente del acuífero. Los resultados obtenidos presentan una precisión general del 94.7%. Su evaluación aporta un error medio cuadrático de 0.163 y R-cuadrado de 0.874. La alta precisión y los bajos niveles de error obtenidos permiten validar la metodología empleada, que presenta potencial de mejora mediante una mayor alimentación del proceso de aprendizaje automático, que se aplicará en breve a otros cultivos leñosos