Hemangioendotelioma epiteloide óseo multicentrico : a propósito de un caso

El Hemangioendotelioma epiteloide óseo (HEEO) es un tumor vascular, infrecuente, con apariencia epiteloide que si no se conoce, puede confundirse con un carcinoma metastásico. Presentamos un caso de HEEO que por las características clínicas del paciente, se podría confundir con lesiones metastásicas de un carcinoma de origen desconocido. Se han descrito pocos casos de HEEO. Clínicamente el tumor cursa con un crecimiento lento y aunque el comportamiento es benigno, se han descrito metástasis a diversos niveles. Suele ser de loralización multicéntrica, teniendo especial predilección en los huesos de una extremidad. Esta característica hace necesaria una cirugía radical en estos pacientes. En nuestro caso el tratamiento realizado, aunque agresivo, fue efectivo, ya que el paciente ha vuelto a su actividad normal, una vez implantada la ortesis.The epitheloid hemangioendothelioma of bone is an infrequent vascular tumor which can be often mistaken for a metastatic carcinoma. We report a case mistaken for a metastatic carcinoma of unknown origin due to the clinical characteristics of the patient. To date, few cases of epitheloid hemangioendothelioma of bone have been described. The tumor shows a low growth rate. Although the tumor has a benign behavior, cases with metastatic spreadming have been reported. Often the tumor is multicentric with special affinitty for the bones of the extremities. This fact allows radial surgery as the best treatment choice. In our case the treatment, supracondylar amputation, was aggresive but effective, since the patient returned to his daily activities after application of the orthesis

Intelligent SPARQL Endpoints: Optimizing Execution Performance by Automatic Query Relaxation and Queue Scheduling

The Web of Data is widely considered as one of the major global repositories populated with countless interconnected and struc- tured data prompting these linked datasets to be continuously and sharply increasing. In this context the so-called SPARQL Protocol and RDF Query Language is commonly used to retrieve and manage stored data by means of SPARQL endpoints, a query processing service especially designed to get access to these databases. Nevertheless, due to the large amount of data tackled by such endpoints and their structural complex- ity, these services usually suffer from severe performance issues, including inadmissible processing times. This work aims at overcoming this noted inefficiency by designing a distributed parallel system architecture that improves the performance of SPARQL endpoints by incorporating two functionalities: 1) a queuing system to avoid bottlenecks during the exe- cution of SPARQL queries; and 2) an intelligent relaxation of the queries submitted to the endpoint at hand whenever the relaxation itself and the consequently lowered complexity of the query are beneficial for the over- all performance of the system. To this end the system relies on a two-fold optimization criterion: the minimization of the query running time, as predicted by a supervised learning model; and the maximization of the quality of the results of the query as quantified by a measure of similar- ity. These two conflicting optimization criteria are efficiently balanced by two bi-objective heuristic algorithms sequentially executed over groups of SPARQL queries. The approach is validated on a prototype and several experiments that evince the applicability of the proposed scheme

Residence time effects on the NOx removal efficiency in two different dielectric barrier discharge cell

Experimental tests of the removal of NOx compounds were carried out in two dielectric barrier discharge cells (DBD) reactors. Two different geometries of these reactor were studied, one circular 11.94 cm diameter, and another rectangular, 16x7cm, both 2.5mm gap and 28.0cm3 reaction volume. A gas mixture composed of 1.0 l/m of molecular nitrogen was injected to each reactor along with an additional flow that provided a concentration of 90ppm of NO in both cells. The gas mixture was treated with non –thermal plasma generated by dielectric barrier discharge at different working potentials and at a 1.75 kHz frequency. The residual products were identified by means of a Sensonic 2000 gas analyzer. According to the experimental results, it was identified a greater removal efficiency in the rectangular cell than in thecircular one. This might be attributed both to residence time due to geometric effects and to a factor related with the chemical reaction mechanisms, since it has been showed that, at greater powers, the removal efficiency diminishes due to the regeneration of NO by inverse kinetic mechanisms. Our kinetic model proves that the main reaction product was N2O in the presence of are ducing atmosphere

Detection of non-technical losses in smart meter data based on load curve profiling and time series analysis

The advent and progressive deployment of the so-called Smart Grid has unleashed a profitable portfolio of new possibilities for an efficient management of the low-voltage distribution network supported by the introduction of information and communication technologies to exploit its digitalization. Among all such possibilities this work focuses on the detection of anomalous energy consumption traces: disregarding whether they are due to malfunctioning metering equipment or fraudulent purposes, strong efforts are invested by utilities to detect such outlying events and address them to optimize the power distribution and avoid significant income costs. In this context this manuscript introduce a novel algorithmic approach for the identification of consumption outliers in Smart Grids that relies on concepts from probabilistic data mining and time series analysis. A key ingredient of the proposed technique is its ability to accommodate time irregularities – shifts and warps – in the consumption habits of the user by concentrating on the shape of the consumption rather than on its temporal properties. Simulation results over real data from a Spanish utility are presented and discussed, from where it is concluded that the proposed approach excels at detecting different outlier cases emulated on the aforementioned consumption traces.Ministerio de Energía y Competitividad under the RETOS program (OSIRIS project, grant ref. RTC-2014-1556-3)

β-adrenergic-mediated dynamic augmentation of sarcolemmal CaV 1.2 clustering and co-operativity in ventricular myocytes.

Key pointsPrevailing dogma holds that activation of the β-adrenergic receptor/cAMP/protein kinase A signalling pathway leads to enhanced L-type CaV 1.2 channel activity, resulting in increased Ca2+ influx into ventricular myocytes and a positive inotropic response. However, the full mechanistic and molecular details underlying this phenomenon are incompletely understood. CaV 1.2 channel clusters decorate T-tubule sarcolemmas of ventricular myocytes. Within clusters, nanometer proximity between channels permits Ca2+ -dependent co-operative gating behaviour mediated by physical interactions between adjacent channel C-terminal tails. We report that stimulation of cardiomyocytes with isoproterenol, evokes dynamic, protein kinase A-dependent augmentation of CaV 1.2 channel abundance along cardiomyocyte T-tubules, resulting in the appearance of channel 'super-clusters', and enhanced channel co-operativity that amplifies Ca2+ influx. On the basis of these data, we suggest a new model in which a sub-sarcolemmal pool of pre-synthesized CaV 1.2 channels resides in cardiomyocytes and can be mobilized to the membrane in times of high haemodynamic or metabolic demand, to tune excitation-contraction coupling.AbstractVoltage-dependent L-type CaV 1.2 channels play an indispensable role in cardiac excitation-contraction coupling. Activation of the β-adrenergic receptor (βAR)/cAMP/protein kinase A (PKA) signalling pathway leads to enhanced CaV 1.2 activity, resulting in increased Ca2+ influx into ventricular myocytes and a positive inotropic response. CaV 1.2 channels exhibit a clustered distribution along the T-tubule sarcolemma of ventricular myocytes where nanometer proximity between channels permits Ca2+ -dependent co-operative gating behaviour mediated by dynamic, physical, allosteric interactions between adjacent channel C-terminal tails. This amplifies Ca2+ influx and augments myocyte Ca2+ transient and contraction amplitudes. We investigated whether βAR signalling could alter CaV 1.2 channel clustering to facilitate co-operative channel interactions and elevate Ca2+ influx in ventricular myocytes. Bimolecular fluorescence complementation experiments reveal that the βAR agonist, isoproterenol (ISO), promotes enhanced CaV 1.2-CaV 1.2 physical interactions. Super-resolution nanoscopy and dynamic channel tracking indicate that these interactions are expedited by enhanced spatial proximity between channels, resulting in the appearance of CaV 1.2 'super-clusters' along the z-lines of ISO-stimulated cardiomyocytes. The mechanism that leads to super-cluster formation involves rapid, dynamic augmentation of sarcolemmal CaV 1.2 channel abundance after ISO application. Optical and electrophysiological single channel recordings confirm that these newly inserted channels are functional and contribute to overt co-operative gating behaviour of CaV 1.2 channels in ISO stimulated myocytes. The results of the present study reveal a new facet of βAR-mediated regulation of CaV 1.2 channels in the heart and support the novel concept that a pre-synthesized pool of sub-sarcolemmal CaV 1.2 channel-containing vesicles/endosomes resides in cardiomyocytes and can be mobilized to the sarcolemma to tune excitation-contraction coupling to meet metabolic and/or haemodynamic demands

On the Creation of Diverse Ensembles for Nonstationary Environments using Bio-inspired Heuristics

Recently the relevance of adaptive models for dynamic data environments has turned into a hot topic due to the vast number of sce- narios generating nonstationary data streams. When a change (concept drift) in data distribution occurs, the ensembles of models trained over these data sources are obsolete and do not adapt suitably to the new distribution of the data. Although most of the research on the field is focused on the detection of this drift to re-train the ensemble, it is widely known the importance of the diversity in the ensemble shortly after the drift in order to reduce the initial drop in accuracy. In a Big Data sce- nario in which data can be huge (and also the number of past models), achieving the most diverse ensemble implies the calculus of all possible combinations of models, which is not an easy task to carry out quickly in the long term. This challenge can be formulated as an optimization prob- lem, for which bio-inspired algorithms can play one of the key roles in these adaptive algorithms. Precisely this is the goal of this manuscript: to validate the relevance of the diversity right after drifts, and to un- veil how to achieve a highly diverse ensemble by using a self-learning optimization technique

A novel adaptive density-based ACO algorithm with minimal encoding redundancy for clustering problems

In the so-called Big Data paradigm descriptive analytics are widely conceived as techniques and models aimed at discovering knowledge within unlabeled datasets (e.g. patterns, similarities, etc) of utmost help for subsequent predictive and prescriptive methods. One of these techniques is clustering, which hinges on different multi-dimensional measures of similarity between unsupervised data instances so as to blindly collect them in groups of clusters. Among the myriad of clustering approaches reported in the literature this manuscript focuses on those relying on bio-inspired meta-heuristics, which have been lately shown to outperform traditional clustering schemes in terms of convergence, adaptability and parallelization. Specifically this work presents a new clustering approach based on the processing fundamentals of the Ant Colony Optimization (ACO) algorithm, i.e. stigmergy via pheromone trails and progressive construction of solutions through a graph. The novelty of the proposed scheme beyond previous research on ACO-based clustering lies on a significantly pruned graph that not only minimizes the representation redundancy of the problem at hand, but also allows for an embedded estimation of the number of clusters within the data. However, this approach imposes a modified ant behavior so as to account for the optimality of entire paths rather than that of single steps within the graph. Simulation results over conventional datasets will evince the promising performance of our approach and motivate further research aimed at its applicability to real scenarios

Specialized business incubators as a strategy for small and medium-sized enterprises in the industry 4.0 era – a systemic approach

The present research aims to get a holistic view of the characteristics of specialization in business incubators models. This paper centers on building a general framework by taking into account a holistic look at the features, profiles, advantages, and disadvantages of specialization in business incubators models. The strategy aims to impact mainly stakeholders by adopting business incubators strategies, especially to those tenant firms of the manufacturing sector related to emerging technologies such as Industry 4.0 technologies. Moreover, the framework is built based on the discussion of the leading representatives' heads of the specialization in the field of specialized business incubators' models. The strategy aims to reduce the current short-term death rate expectancy prevailing in the contemporary economic context by a robust business model for business incubation. Business incubators hold tenants into a hub with not only supportive facilities for the business without investing vital capital, which is not part of their core chain value but also harnessing the closer source of knowledge transfer and skilfully workforce-related on these technologies. Finally, remarks and recommendations are proposed for futures tenant companies' prospects, who wish to reduce the bankruptcy risk by boosting innovative goods and services with high technological development in a specific field of knowledge.N/

A retrospective analysis of policy development on compliance with World Health Organization's physical activity recommendations between 2002 and 2005 in European Union adults: Closing the gap between research and policy

© 2018 The Author(s). Background: Physical inactivity (PIA) is a mortality risk factor defined as performing lower levels of physical activity than recommended by the World Health Organization (WHO). After 2002, the WHO released the WHA55.23 Resolution and the Global Strategy which produced several changes in policymaking, but with no subsequent analyses of the impact of these changes in European Union (EU) policymaking while examining PIA prevalence. Methods: PIA of 31,946 adults as a whole sample and country-by-country were analyzed in the 2002 and 2005 EU Special Eurobarometers. PIA prevalence between countries was performed with the χ2 test and PIA between both years and between genders was analyzed with the Z-Score test for two population proportions. A retrospective analysis of national plans was performed to interpret the suitability of such policy documents, considering changes in PIA prevalence. Results: Differences in PIA prevalence were observed between countries (p 0.05). When considering gender, there were no gender reductions in subsamples for Denmark, Finland, Ireland, Portugal, Spain, and United Kingdom, neither in Luxemburg for men, nor in France and Italy for women. When analyzing gender differences across the entire sample, PIA was higher in women than men for both years (p < 0.001). Greece and Luxemburg did not release national plans for promoting physical activity. Conclusions: While large differences in PIA prevalence between EU countries prevailed, the overall PIA descended between both years for the whole sample, men, and women. While this points out a general suitability of policymaking for reducing PIA, not all countries reported reductions in PIA for men, women, or both genders. Also, PIA levels were higher for women in both years, suggesting a less than optimal policy implementation, or lack of women-specific focus across the EU. This analysis helps to identify the strengths and weaknesses of PIA policymaking in the EU and provides researchers with targeted intervention areas for future development