Estado actual de la investigación sobre la teoría tridimensional de la ansiedad de Lang

Este estudio ofrece una revisión de la teoría tridimensional propuesta por Lang (1968), quien mantiene que la ansiedad se manifiesta según un triple sistema de respuesta (cognitivo, fisiológico y motor o conductual) que pueden ser discordantes. Estos tres sistemas, regulados por normas diferentes, dan lugar a perfiles de respuesta diferenciales, los cuales será necesario evaluar por separado para, posteriormente, elegir el método de tratamiento más adecuado. En esta línea, el presente estudio ofrece una revisión de investigaciones que, hasta el día de hoy, han apoyado la teoría propuesta por Lang. Finalmente, este estudio revisa diferentes cuestionarios, inventarios y escalas construidos desde la teoría propuesta por Lang, revelando que, en la actualidad, la teoría tridimensional de la ansiedad continúa siendo aplicada en el ámbito clínico, de la salud y el escolar, lo que denota su actualidad, relevancia y practicidad.

Geometrical study of the three-dimensional temperature–composition diagrams. An important aid to understand the behavior of the liquid–vapour equilibrium in ternary systems

In this work the usefulness of qualitatively studying and drawing three-dimensional temperature–composition diagrams for ternary systems is pointed out to understand and interpret the particular behavior of the liquid–vapour equilibrium of non-ideal ternary systems. Several examples have been used in order to highlight the interest and the possibilities of this tool, which should be an interesting support not only for lecturers, but also for researchers interested in experimental equilibrium data determination.

Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which can estimate multiple plane models simultaneously from a noisy point cloud using the knowledge extracted from a scene (or an object) in order to reconstruct it accurately. This method comprises two steps: first, it clusters the data into planar faces that preserve some constraints defined by knowledge related to the object (e.g., the angles between faces); and second, the models of the planes are estimated based on these data using a novel multi-constraint RANSAC. We performed experiments in the clustering and RANSAC stages, which showed that the proposed method performed better than state-of-the-art methods.

Three-dimensional planar object tracking with sub-pixel accuracy

Subpixel techniques are commonly used to increase the spatial resolution in tracking tasks. Object tracking with targets of known shape permits obtaining information about object position and orientation in the three-dimensional space. A proper selection of the target shape allows us to determine its position inside a plane and its angular and azimuthal orientation under certain limits. Our proposal is demonstrated both numerical and experimentally and provides an increase the accuracy of more than one order of magnitude compared to the nominal resolution of the sensor. The experiment has been performed with a high-speed camera, which simultaneously provides high spatial and temporal resolution, so it may be interesting for some applications where this kind of targets can be attached, such as vibration monitoring and structural analysis.

A three-dimensional representation method for noisy point clouds based on growing self-organizing maps accelerated on GPUs

The research described in this thesis was motivated by the need of a robust model capable of representing 3D data obtained with 3D sensors, which are inherently noisy. In addition, time constraints have to be considered as these sensors are capable of providing a 3D data stream in real time. This thesis proposed the use of Self-Organizing Maps (SOMs) as a 3D representation model. In particular, we proposed the use of the Growing Neural Gas (GNG) network, which has been successfully used for clustering, pattern recognition and topology representation of multi-dimensional data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models, without considering time constraints. It is proposed a hardware implementation leveraging the computing power of modern GPUs, which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). The proposed methods were applied to different problem and applications in the area of computer vision such as the recognition and localization of objects, visual surveillance or 3D reconstruction.

Polarized interacting exciton gas in quantum wells and bulk semiconductors

We develop a theory to calculate exciton binding energies of both two- and three-dimensional spin polarized exciton gases within a mean field approach. Our method allows the analysis of recent experiments showing the importance of the polarization and intensity of the excitation light on the exciton luminescence of GaAs quantum wells. We study the breaking of the spin degeneracy observed at high exciton density (5×1010 cm2). Energy level splitting between spin +1 and spin -1 is shown to be due to many-body interexcitonic exchange while the spin relaxation time is controlled by intraexciton exchange. © 1996 The American Physical Society.

Evidence of Intracrystalline Mesostructured Porosity in Zeolites by Advanced Gas Sorption, Electron Tomography and Rotation Electron Diffraction

The small size of micropores (typically <1 nm) in zeolites causes slow diffusion of reactant and product molecules in and out of the pores and negatively impacts the product selectivity of zeolite based catalysts, for example, fluid catalytic cracking (FCC) catalysts. Size-tailored mesoporosity was introduced into commercial zeolite Y crystals by a simple surfactant-templating post-synthetic mesostructuring process. The resulting mesoporous zeolite Y showed significantly improved product selectivity in both laboratory testing and refinery trials. Advanced characterization techniques such as electron tomography, three-dimensional rotation electron diffraction, and high resolution gas adsorption coupled with hysteresis scanning and density functional theory, unambiguously revealed the intracystalline nature and connectivity of the introduced mesopores. They can be considered as molecular highways that help reactant and product molecules diffuse quickly to and away from the catalytically active sites within the zeolite crystals and, thus, shift the selectivity to favor the production of more of the valuable liquid fuels at reduced yields of coke and unconverted feed.

Cálculo del asiento elástico tridimensional de cimentaciones de rigidez variable en terrenos con una capa rígida inclinada

Las fórmulas basadas en la teoría de la elasticidad son ampliamente utilizadas para el cálculo de asientos de cimentaciones, ya que la totalidad de la normativa geotécnica recomienda su empleo. No obstante, estos métodos no cubren todas las situaciones geotécnicamente posibles ya que frecuentemente las condiciones geológicas son complejas. En este trabajo se analiza la influencia de la presencia de una capa rígida inclinada en los asientos elásticos de una cimentación superficial. Para ello se han resuelto 273 modelos tridimensionales no lineales de elementos finitos, variando los parámetros clave del problema: la inclinación y la profundidad de la capa rígida y la rigidez de la cimentación. Finalmente, se ha realizado un análisis estadístico de los resultados de los modelos y se ha propuesto una fórmula que puede ser utilizada en el cálculo de asientos por métodos elásticos, para tener en consideración la presencia de una capa rígida inclinada en profundidad.