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El presente trabajo describe una nueva metodología docente basada en lasúltimas investigaciones científicas orientadas a la reconstrucción tridimensional de soldaduras, las cuales permiten la generación de paquetes de trabajo dirigidos a la adquisición de competencias propias de actividades de laboratorio de soldadura sin necesidad de que exista un desplazamiento físico al mismo. Esta metodología, que puede ser catalogada dentro de las basadas en laboratorios virtuales (LVs), es de aplicación en programas semipresenciales, e-learning o también puede utilizarse como material de apoyo a los programas presenciales, principalmente en las titulaciones relacionadas con la ingeniería industrial, naval y aeronáutica, así como las ingenierías más relacionadas con la geomática y la informática. La distribución de los paquetes es de fácil implementación a través de plataformas virtuales de formación y el trabajo con los modelos puede realizarse con software libre o gratuito, sin necesidad de costes adicionales para las entidades de formación que los utilicen. Abstract-The present work describes a new teaching methodology based on the latest research oriented to the threedimensional reconstruction of welds that allows the generation of work packages aimed at the acquisition of competences specific to welding lab activities without the need for a physical same. This methodology, which can be cataloged within the methodologies based on virtual laboratories (LVs), is applicable in e-learning programs or can also be used as support material for face-to-face programs, mainly in the degree programs related to Industrial, naval and aeronautical engineering, as well as engineering related to geomatics and computer science. The distribution of the packages is easy to implement through virtual training platforms and the work with the models can be done with open or free software, without the need of additional costs for the training entities that use them.

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SUMMARYA proven case of human infection caused by Angiostrongylus costaricensis is reported for the first time in Venezuela. The patient was a 57-year-old female surgically operated because of signs of peritonitis with a palpable mass at the lower right quadrant of the abdomen. WBC count reported 16,600 cells/mm 3 , with 46% eosinophils. The tumoral aspect of ileocolic area and peritoneal lymph nodes prompted the resection of a large area of the terminal ileum, cecum, part of the ascending colon and a small part of the jejunum, where a small lesion was found. The pathology showed thickened areas of the intestinal wall with areas of hemorrhage and a perforation of the cecum. Histology showed intense eosinophil infiltration of the whole intestinal wall, granulomas with giant cells and eosinophils. Some of the granuloma surrounded round or oval eggs with content characterized by a large empty area, cells or embryo in the center, and sometimes nematode larvae. A cross section of an adult nematode worm was observed inside a branch of mesenteric artery. The intestinal affected area, the characteristics of the lesions, the presence of eggs in the submucosa with nematode larvae inside, and the observation of a nematode inside a mesenteric artery, makes sufficient criteria for the diagnosis of an infection by Angiostrongylus costaricensis.

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Weld bead detection is essential for automated welding inspection processes. The non-invasive passive techniques, such as photogrammetry, are quickly evolving to provide a 3D point cloud with submillimeter precision and spatial resolution. However, its application in weld visual inspection has not been extensively studied. The derived 3D point clouds, despite the lack of topological information, store significant information for the weld-plaque segmentation. Although the weld bead detection is being carried out over images or based on laser profiles, its characterization by means of 3D geometrical features has not been assessed. Moreover, it is possible to combine machine learning approaches and the 3D features in order to realize the full potential of the weld bead segmentation of 3D submillimeter point clouds. In this paper, the novelty is focused on the study of 3D features on real cases to identify the most relevant ones for weld bead detection on the basis of the information gain. For this novel contribution, the influence of neighborhood size for covariance matrix computation, decision tree algorithms, and split criteria are analyzed to assess the optimal results. The classification accuracy is evaluated by the degree of agreement of the classified data by the kappa index and the area under the receiver operating characteristic (ROC) curve. The experimental results show that the proposed novel methodology performs better than 0.85 for the kappa index and better than 0.95 for ROC area.