La barca de piedra de San Juan de la Misarela: Características, paralelos y origen de una embarcación legendaria

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El espíritu del grano: Tradiciones agrícolas propiciatorias en Galicia y en otras comunidades europeas

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Nuevas consideraciones sobre el significado del perroglifo de Laxe das Rodas (Muros, Galicia)

La primera exposición pública de mi interpretación del significado del petroglifo de Laxe das Rodas tuvo lugar en la 1.a Reunión Gallega de Estudios Clásicos, celebrada en Santiago de Compostela en julio de 1979- En este mismo Congreso, L. Monteagudo presentó también un detenido estudio sobre los orígenes y paralelos de dicho petroglifo en otras áreas culturales

A computational comparison of several formulations for the multi-period incremental service facility location problem

The Multi-period Incremental Service Facility Location Problem, which was recently introduced, is a strategic problem for timing the location of facilities and the assignment of customers to facilities in a multi-period environment. Aiming at finding the strongest formulation for this problem, in this work we study three alternative formulations based on the so-called impulse variables and step variables. To this end, an extensive computational comparison is performed. As a conclusion, the hybrid impulse–step formulation provides better computational results than any of the other two formulations

Thermodynamics of binary mixtures 1-ethoxy-1,1,2,2,3,3,4,4,4-nonafluorobutane (HFE-7200) + 2-propanol: High pressure density, speed of sound and derivative properties

Awareness about environmental impact of greenhouse gas emissions has lead to search for other alternatives which can cover the same utility range of wellknown CFCs, HCFCs and PFCs but without their undesirable effects on the planet. Since Hydrofluoroether fluids (HFEs) have emerged as a good alternative, it is necessary to characterize their thermophysical properties in order to bring reliable data to the industry. Density and speed of sound are two of the most important physical properties because of the amount of information that they provide in the design of the machinery involved in the utilization of these fluids as well as data for the parametrization of equations of state. This paper reports a set of new data concerning high pressure density, ρ, for the binary mixture x HFE-7200 + (1 − x) 2-propanol in a broad range of pressures (0.1–140 MPa), and at several temperatures (from 293.15 to 393.15 K). Density values were correlated by employing a Tait-like equation in the same p, T ranges, and the derivative properties, that is, the isothermal compressibility κT, and the isobaric expansion αP, were determined. Excess molar volumes VE, which bring information about the change in volume observed in the mixture were also calculated for the eight mole fractions investigated. Speeds of sound, c, at 0.1 MPa were measured experimentally in the temperature range (293.15–333.15 K). By using the Laplace equation, isentropic compressibilities, κS, were calculated from density and sound velocity values

Automatic detection of colorectal polyps using artificial intelligence techniques

Colorectal cancer (CRC) is one of the most prevalent malignant tumors in Colombia and the world. These neoplasms originate in adenomatous lesions or polyps that must be resected to prevent the disease, which can be done with a colonoscopy. It has been reported that during colonoscopy polyps are detected in 40% of men and 30% of women (hyperplastic, adenomatous, serrated, among others), and, on average, 25% of adenomatous polyps (main quality indicator in colonoscopy). However, these lesions are not easy to observe due to the multiplicity of blind spots in the colon and the human error associated with the examination. Objective: to create a computational method for the automatic detection of colorectal polyps using artificial intelligence in recorded videos of real colonoscopy procedures. Methodology: public databases with colorectal polyps and a data collection built in a University Hospital were used. Initially, all the frames of the videos were normalized to reduce the high variability between databases. Subsequently, the polyp detection task is done with a deep learning method using a convolutional neural network. This network is initialized with weights learned on millions of national images from the ImageNet database. The weights of the network are updated using colonoscopy images, following the tuning technique.