Racionalismo y racionalización de la vivienda colectiva en España 1925 - 1939

A partir de 1925 en un creciente contexto de cambio social y político en el estado español se introducen una serie de nuevas ideas procedentes de Europa que fomentan la renovación del ecléctico panorama arquitectónico español mediante una nueva imagen formal, la introducción de nuevos materiales y sistemas constructivos, así como de un diseño despojado de las normas académicas del pasado. Este proceso de renovación arquitectónico motivará una serie de propuestas dirigidas a racionalizar la vivienda urbana, planteando la ruptura respecto al modelo existente. El alcance de estas propuestas se verá influido y condicionado por los grandes programas de vivienda desarrollados en Europa, la situación del alojamiento en las grandes ciudades, el papel de las autoridades respecto a este problema o el agitado contexto político y social en España. En este ambiente surge un grupo de jóvenes arquitectos, el GATEPAC (Grupo de Arquitecto y Técnicos Españoles para el Progreso de la Arquitectura Contemporánea), que difunden y adaptan los postulados racionalistas a la realidad española. De este modo encabezarán las nuevas corrientes renovadoras dirigiendo sus propuestas a la transformación de su entorno más inmediato, buscando soluciones a los principales problemas sociales de la época como son la sanidad, la educación, el ocio, el descanso, la ciudad y la vivienda. Con el objetivo de valorar el alcance de este proceso de modernización de la vivienda colectiva se analizarán los planteamientos desarrollados por el GATEPAC en torno a esta tipología así como las principales obras materializadas durante este periodo. Esta primera etapa racionalista en España será interrumpida finalmente por la Guerra Civil y el inicio del régimen franquista, que retrasaría la generalización de las novedades ensayadas por este grupo de arquitectos. Una labor que aún hoy ejerce una importante influencia en las propuestas actuales.

Faster Optimization in S-Graphs Exploiting Hierarchy

3D scene graphs hierarchically represent the environment appropriately organizing different environmental entities in various layers. Our previous work on situational graphs extends the concept of 3D scene graph to SLAM by tightly coupling the robot poses with the scene graph entities, achieving state-of-the-art results. Though, one of the limitations of S-Graphs is scalability in really large environments due to the increased graph size over time, increasing the computational complexity. To overcome this limitation in this work we present an initial research of an improved version of S-Graphs exploiting the hierarchy to reduce the graph size by marginalizing redundant robot poses and their connections to the observations of the same structural entities. Firstly, we propose the generation and optimization of room-local graphs encompassing all graph entities within a room-like structure. These room-local graphs are used to compress the S-Graphs marginalizing the redundant robot keyframes within the given room. We then perform windowed local optimization of the compressed graph at regular time-distance intervals. A global optimization of the compressed graph is performed every time a loop closure is detected. We show similar accuracy compared to the baseline while showing a 39.81% reduction in the computation time with respect to the baseline.Comment: 4 pages, 3 figures, IROS 2023 Workshop Pape

S-Graphs+: Real-time Localization and Mapping leveraging Hierarchical Representations

In this paper, we present an evolved version of the Situational Graphs, which jointly models in a single optimizable factor graph, a SLAM graph, as a set of robot keyframes, containing its associated measurements and robot poses, and a 3D scene graph, as a high-level representation of the environment that encodes its different geometric elements with semantic attributes and the relational information between those elements. Our proposed S-Graphs+ is a novel four-layered factor graph that includes: (1) a keyframes layer with robot pose estimates, (2) a walls layer representing wall surfaces, (3) a rooms layer encompassing sets of wall planes, and (4) a floors layer gathering the rooms within a given floor level. The above graph is optimized in real-time to obtain a robust and accurate estimate of the robot's pose and its map, simultaneously constructing and leveraging the high-level information of the environment. To extract such high-level information, we present novel room and floor segmentation algorithms utilizing the mapped wall planes and free-space clusters. We tested S-Graphs+ on multiple datasets including, simulations of distinct indoor environments, on real datasets captured over several construction sites and office environments, and on a real public dataset of indoor office environments. S-Graphs+ outperforms relevant baselines in the majority of the datasets while extending the robot situational awareness by a four-layered scene model. Moreover, we make the algorithm available as a docker file.Comment: 8 Pages, 7 Figures, 3 Table

Permittivity Spectrum of Low-Loss Liquid and Powder Geomaterials Using Multipoint Reentrant Cavities

[EN] Permittivity is a useful tool to characterize the composition and quality of many geomaterials. In general, the non-resonant permittivity measurement methods exhibit a higher degree of uncertainty than their resonant counterparts. In resonant measurements, the reduction in uncertainty comes typically with a loss in broadband. This article describes the theory, design, and application of multipoint coaxial reentrant resonant cavities applied to low-loss geomaterials at different temperatures. Specifically, a full-wave method based on circuit analysis is developed and applied for a circular corrugated waveguide. Moreover, the mode-matching method is applied to calculate the generalized admittance matrix (GAM). Two multipoint cavities and software were built and validated. The first cavity has five resonant frequencies, between 170 MHz and 2.3 GHz, and the second has four resonant frequencies, between 1.3 and 8.6 GHz. Thus, this method allows for ¿broadband-resonant¿ measurements. The permittivity values of liquid hydrocarbons, powdered kerogen, and pyrite are shown.Alvarez, JO.; Penaranda-Foix, FL.; Catalá Civera, JM.; Gutiérrez Cano, JD. (2020). Permittivity Spectrum of Low-Loss Liquid and Powder Geomaterials Using Multipoint Reentrant Cavities. IEEE Transactions on Geoscience and Remote Sensing. 58(5):3097-3112. https://doi.org/10.1109/TGRS.2019.2948052S3097311258

Coronavirus disease 2019 in chronic kidney disease

The clinical spectrum of coronavirus disease 2019 (COVID-19) infection ranges from asymptomatic infection to severe pneumonia with respiratory failure and even death. More severe cases with higher mortality have been reported in older patients and in those with chronic illness such as hypertension, diabetes or cardiovascular diseases. In this regard, patients with chronic kidney disease (CKD) have a higher rate of all-type infections and cardiovascular disease than the general population. A markedly altered immune system and immunosuppressed state may predispose CKD patients to infectious complications. Likewise, they have a state of chronic systemic inflammation that may increase their morbidity and mortality. In this review we discuss the chronic immunologic changes observed in CKD patients, the risk of COVID-19 infections and the clinical implications for and specific COVID-19 therapy in CKD patients. Indeed, the risk for severe COVID-19 is 3-fold higher in CKD than in non-CKD patients; CKD is 12-fold more frequent in intensive care unit than in non-hospitalized COVID-19 patients, and this ratio is higher than for diabetes or cardiovascular disease; and acute COVID19 mortality is 15-25% for haemodialysis patients even when not developing pneumonia

Feasible glass-melting process assisted by microwaves

This is the peer reviewed version of the following article: Reinosa, JJ, García-Baños, B, Catalá-Civera, JM, López-Buendía, AM, Guaita, L, Fernández, JF. Feasible glass-melting process assisted by microwaves. Int J Appl Glass Sci. 2019; 10: 208 219, which has been published in final form at https://doi.org/10.1111/ijag.13093. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.[EN] The advantages of microwave (MW) energy processing have been verified in the sintering of a ceramic frit at a pre-industrial scale. The challenge of achieving high temperature using MW energy at such dimensions was overcome and a mix of natural raw materials was heated until its fluxing point. Changes in dielectric properties of the raw materials mix were also measured in situ with the increase in temperature, being in accordance to thermal processes of a conventional heating process. The properties of the resulting ceramic frit were compared with the same frit obtained by the conventional sintering method. Both frits showed similar thermal behavior regarding DTA-TGA, heating microscopy and XRD (only glassy phase was present). A Raman study confirms the existence of the mentioned glass phase. The application of the frits as glazes were performed and their properties were studied. As a result, glazes with similar properties were obtained which confirms that the MW energy processed frit is suitable for its application as a ceramic glaze.Consejo Superior de Investigaciones Cientificas, Grant/Award Number: CSIC201560E068; Ministerio de Ciencia, Tecnologia e Innovacion Productiva, Grant/Award Number: MAT2017-86450-C4-1-R; Seventh Framework Programme, Daphne Project, Grant/Award Number: 314636Jiménez Reinosa, J.; García-Baños, B.; Catalá Civera, JM.; López-Buendía, ÁM.; Guaita, L.; Fernández, JF. (2019). Feasible glass-melting process assisted by microwaves. International Journal of Applied Glass Science. 10(2):208-219. https://doi.org/10.1111/ijag.13093S20821910

Advanced Situational Graphs for Robot Navigation in Structured Indoor Environments

Mobile robots extract information from its environment to understand their current situation to enable intelligent decision making and autonomous task execution. In our previous work, we introduced the concept of Situation Graphs (S-Graphs) which combines in a single optimizable graph, the robot keyframes and the representation of the environment with geometric, semantic and topological abstractions. Although S-Graphs were built and optimized in real-time and demonstrated state-of-the-art results, they are limited to specific structured environments with specific hand-tuned dimensions of rooms and corridors. In this work, we present an advanced version of the Situational Graphs (S-Graphs+), consisting of the five layered optimizable graph that includes (1) metric layer along with the graph of free-space clusters (2) keyframe layer where the robot poses are registered (3) metric-semantic layer consisting of the extracted planar walls (4) novel rooms layer constraining the extracted planar walls (5) novel floors layer encompassing the rooms within a given floor level. S-Graphs+ demonstrates improved performance over S-Graphs efficiently extracting the room information while simultaneously improving the pose estimate of the robot, thus extending the robots situational awareness in the form of a five layered environmental model.

Situational Graphs for Robot Navigation in Structured Indoor Environments

Mobile robots should be aware of their situation, comprising the deep understanding of their surrounding environment along with the estimation of its own state, to successfully make intelligent decisions and execute tasks autonomously in real environments. 3D scene graphs are an emerging field of research that propose to represent the environment in a joint model comprising geometric, semantic and relational/topological dimensions. Although 3D scene graphs have already been combined with SLAM techniques to provide robots with situational understanding, further research is still required to effectively deploy them on-board mobile robots. To this end, we present in this paper a novel, real-time, online built Situational Graph (S-Graph), which combines in a single optimizable graph, the representation of the environment with the aforementioned three dimensions, together with the robot pose. Our method utilizes odometry readings and planar surfaces extracted from 3D LiDAR scans, to construct and optimize in real-time a three layered S-Graph that includes (1) a robot tracking layer where the robot poses are registered, (2) a metric-semantic layer with features such as planar walls and (3) our novel topological layer constraining the planar walls using higher-level features such as corridors and rooms. Our proposal does not only demonstrate state-of-the-art results for pose estimation of the robot, but also contributes with a metric-semantic-topological model of the environmentComment: 8 pages, 6 figures, RAL/IROS 202