On autonomic platform-as-a-service: characterisation and conceptual model

In this position paper, we envision a Platform-as-a-Service conceptual and architectural solution for large-scale and data intensive applications. Our architectural approach is based on autonomic principles, therefore, its ultimate goal is to reduce human intervention, the cost, and the perceived complexity by enabling the autonomic platform to manage such applications itself in accordance with highlevel policies. Such policies allow the platform to (i) interpret the application specifications; (ii) to map the specifications onto the target computing infrastructure, so that the applications are executed and their Quality of Service (QoS), as specified in their SLA, enforced; and, most importantly, (iii) to adapt automatically such previously established mappings when unexpected behaviours violate the expected. Such adaptations may involve modifications in the arrangement of the computational infrastructure, i.e. by re-designing a different communication network topology that dictates how computational resources interact, or even the live-migration to a different computational infrastructure. The ultimate goal of these challenges is to (de)provision computational machines, storage and networking links and their required topologies in order to supply for the application the virtualised infrastructure that better meets the SLAs. Generic architectural blueprints and principles have been provided for designing and implementing an autonomic computing system.We revisit them in order to provide a customised and specific viewfor PaaS platforms and integrate emerging paradigms such as DevOps for automate deployments, Monitoring as a Service for accurate and large-scale monitoring, or well-known formalisms such as Petri Nets for building performance models

The effect of scale in daily precipitation hazard assessment

Daily precipitation is recorded as the total amount of water collected by a rain-gauge in 24 h. Events are modelled as a Poisson process and the 24 h precipitation by a Generalised Pareto Distribution (GPD) of excesses. Hazard assessment is complete when estimates of the Poisson rate and the distribution parameters, together with a measure of their uncertainty, are obtained. The shape parameter of the GPD determines the support of the variable: Weibull domain of attraction (DA) corresponds to finite support variables as should be for natural phenomena. However, Fréchet DA has been reported for daily precipitation, which implies an infinite support and a heavy-tailed distribution. Bayesian techniques are used to estimate the parameters. The approach is illustrated with precipitation data from the Eastern coast of the Iberian Peninsula affected by severe convective precipitation. The estimated GPD is mainly in the Fréchet DA, something incompatible with the common sense assumption of that precipitation is a bounded phenomenon. The bounded character of precipitation is then taken as a priori hypothesis. Consistency of this hypothesis with the data is checked in two cases: using the raw-data (in mm) and using log-transformed data. As expected, a Bayesian model checking clearly rejects the model in the raw-data case. However, log-transformed data seem to be consistent with the model. This fact may be due to the adequacy of the log-scale to represent positive measurements for which differences are better relative than absolute

Biplots for compositional data derived from generalized joint diagonalization methods

Biplots constructed from principal components of a compositional data set are an established means to explore its features. Principal Component Analysis (PCA) is also used to transform a set of spatial variables into spatially decorrelated factors. However, because no spatial structures are accounted for in the transformation the application of PCA is limited. In geostatistics and blind source separation a variety of different matrix diagonalization methods have been developed with the aim to provide spatially or temporally decorrelated factors. Just as PCA, many of these transformations are linear and so lend themselves to the construction of biplots. In this contribution we consider such biplots for a number of methods (MAF, UWEDGE and RJD transformations) and discuss how and if they can contribute to our understanding of relationships between the components of regionalized compositions. A comparison of the biplots with the PCA biplot commonly used in compositional data analysis for the case of data from the Northern Irish geochemical survey shows that the biplots from MAF and UWEDGE are comparable as are those from PCA and RJD. The biplots emphasize different aspects of the regionalized composition: for MAF and UWEDGE the focus is the spatial continuity, while for PCA and RJD it is variance explained. The results indicate that PCA and MAF combined provide adequate and complementary means for exploratory statistical analysis

Towards geostatistical learning for the geosciences: A case study in improving the spatial awareness of spectral clustering

The particularities of geosystems and geoscience data must be understood before any development or implementation of statistical learning algorithms. Without such knowledge, the predictions and inferences may not be accurate and physically consistent. Accuracy, transparency and interpretability, credibility, and physical realism are minimum criteria for statistical learning algorithms when applied to the geosciences. This study briefly reviews several characteristics of geoscience data and challenges for novel statistical learning algorithms. A novel spatial spectral clustering approach is introduced to illustrate how statistical learners can be adapted for modelling geoscience data. The spatial awareness and physical realism of the spectral clustering are improved by utilising a dissimilarity matrix based on nonparametric higher-order spatial statistics. The proposed model-free technique can identify meaningful spatial clusters (i.e. meaningful geographical subregions) from multivariate spatial data at different scales without the need to define a model of co-dependence. Several mixed (e.g. continuous and categorical) variables can be used as inputs to the proposed clustering technique. The proposed technique is illustrated using synthetic and real mining datasets. The results of the case studies confirm the usefulness of the proposed method for modelling spatial data

Experimental study on AR fiberglass connectors for bridges made of composite materials

6 páginas, 11 figuras, 1 tabla.[ES] Un aspecto relevante dentro del proyecto de un puenterealizado en materiales compuestos es el estudio de losconectores. El caso mas frecuente de puente en materialescompuestos es aquel que presenta un tablero de materialescompuestos soportado por vigas metalicas o de hormigonarmado. En este trabajo se analizaran los tipos deconectores mas utilizados en este tipo de puentes Se analizaran tambien los conectores utilizados en elKing Stormwater Channel Bridge, donde ademas deltablero en fibra de vidrio, se fabricaron las vigas en fibrasde carbono rellenas de hormigon. En este articulo se propondran varios tipos de conectoresy se presentaran los resultados experimentales correspondientesal ensayo de “push-out” de varios prototipos condiferentes geometrias. Tras evaluar los resultados, se determinara el mas idoneopara su implantacion en el Paso Superior de la Autovia delCantabrico, de 46 metros de luz y que presenta las vigasen fibra de carbono y los conectores de vidrio AR.[EN] One highly relevant aspect in composite material bridge desing is the study of the shear connectors to be used. Composite material bridges most commonly comprise a composite deck resting on steel or reinforced concrete girders. This article analyzes the connectors most frequently used in such bridges. It also reviews the connectors used in the King Stormwater Channel Bridge, whose fibreglass deck is supported by girders made of concrete-filled carbon fibre girders. The paper advances proposals for several types of connectors and discusses the results of push-out test run on a number of prototypes with different geometries. The results are analyzed to identify the optimum model for the “Autovía del Cantábrico” Overpass, with its 46-m span, carbon fibre girders and AR glass shear connectors.Peer reviewe

Diagnostic accuracy of 18F-FDG PET/CT in infective endocarditis and implantable cardiac electronic device infection: A cross-sectional study.

Early diagnosis of infective endocarditis (IE) is based on the yielding of blood cultures and echocardiographic findings. However, they have limitations and sometimes the diagnosis is inconclusive, particularly in patients with prosthetic valves (PV) and implantable cardiac electronic devices (ICED). The primary aim of this study was to evaluate the diagnostic accuracy of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in patients with suspected IE an ICED infection. METHODS: A prospective study with 80 consecutive patients with suspected IE and ICED infection (65 men and 15 women with a mean age of 68±13 years old) between June 2013 and May 2015 was performed in our hospital. The inclusion criteria was clinically suspected IE and ICED infection at the following locations: native valve (NV) (n = 21), PV (n = 29) or ICED (n = 30) [(automatic implantable defibrillator (n = 11) or pacemaker (n = 19)]. Whole-body 18F-FDG PET/CT with a myocardial uptake suppression protocol with unfractionated heparin was performed in all patients. The final diagnosis of infection was established by the IE study Group according to the clinical, echocardiographic and microbiological findings. RESULTS: A final diagnosis of infection was confirmed in 31 patients: NV (n = 6), PV (n = 12) and ICED (n = 13). Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for 18F-FDG PET/CT was 82%, 96%, 94% and 87%, respectively. 18F-FDG PET/CT was false negative in all cases with infected NV. 18F-FDG PET/CT was able to reclassify 63/70 (90%) patients initially classified as possible IE by modified Duke criteria. In 18/70 cases 18F-FDG PET/CT changed possible to definite IE (26%) and in 45/70 cases changed possible to rejected IE (64%). Additionally, 18F-FDG PET/CT identified 8 cases of septic embolism and 3 colorectal cancer in patients with final diagnosis of IE. CONCLUSION: 18F-FDG PET/CT proved to be a useful diagnostic tool in suspected IE and ICED infection and should be included in the diagnostic algorithm for early diagnosis. 18F-FDG PET/CT is not useful in the diagnosis of IE in NV, but should be also considered in the initial assessment of this complex scenario to rule out extracardiac complications and possible neoplasms