Structural Damage Detection and Reliability Estimation using a Multidimensional Monitoring Approach

Many structural elements are exposed to load conditions that are difficult to model during the design stage, such as environmental uncertainties, random impacts and overloading amongst others, thus, increasing un programmed maintenance and reducing..

Observation of magnetic order in the double-layer system La2MCu2O6+δ (M=Ca,Sr)

Under the terms of the Creative Commons Attribution License 3.0 (CC-BY).-- et al.Measurements of the spin rotation and depolarization of implanted positive muons have revealed that La2SrCu2O6+δ, La2CaCu2O6+δ, and La1.9Y0.1CaCu2O6+δ, members of the double-layer perovskite family La2MCu2O6+δ (M=Ca,Sr), display magnetic ordering similar to that of La2−xSrxCuO4−y and YBa2Cu3Ox Their magnetic order parameters are remarkably close to those of the other layered cuprates. A superconducting minority phase has been detected in La2CaCu2O6+δ (δ≥0.02), with onset at ∼45 K and accompanied by a change in the muon-spin-precession signals from the majority antiferromagnetic phase, phenomena absent in La2SrCu2O6+δ. This behavior was attributed to mobility and local clustering of intercalated oxygen excess in the layer between the CuO2 planes.This work was supported by NSERC (Canada), DOE Grant No. DE-FG05-88ER45353, the CICYT and the MIDAS project (Spain), and the CEE.Peer Reviewe

RivFishTIME: A global database of fish time-series as a currency for global change ecology research in riverine systems

Motivation We compiled a global database of long-term riverine fish surveys from 46 regional and national monitoring programmes and from individual academic research efforts, with which numerous basic and applied questions in ecology and global change research can be explored. Such spatially and temporally extensive datasets have been lacking for freshwater systems in comparison to terrestrial ones. Main types of variables contained The database includes 11,386 time-series of riverine fish community catch data, including 646,270 species-specific abundance records, together with metadata related to the geographical location and sampling methodology of each time-series. Spatial location and grain The database contains 11,072 unique sampling locations (stream reach), spanning 19 countries, five biogeographical realms and 402 hydrographical basins world-wide. Time period and grain The database encompasses the period 1951–2019. Each time-series is composed of a minimum of two yearly surveys (mean = 8 years) and represents a minimum time span of 10 years (mean = 19 years). Major taxa and level of measurement The database includes 944 species of ray-finned fishes (Class Actinopterygii). Software format csv. Main conclusion Our collective effort provides the most comprehensive long-term community database of riverine fishes to date. This unique database should interest ecologists who seek to understand the impacts of human activities on riverine fish biodiversity and to model and predict how fish communities will respond to future environmental change. Together, we hope it will promote advances in macroecological research in the freshwater realm

Magnetic states and spin-glass properties in Bi0.67Ca0.33MnO3: macroscopic ac measurements and neutron scattering

We report on the magnetic properties of the manganite Bi_{1-x}Ca_{x}MnO_3 (x=0.33) at low temperature. The analysis of the field expansion of the ac susceptibility and the observation of aging properties make clear that a spin glass phase appears below T = 39K, in the presence of magnetic order. Neutron scattering shows both magnetic Bragg scattering and magnetic diffusion at small angles, and confirms this coexistence. In contrast to Pr_{1-x}Ca_{x}MnO_3 (x=0.3-0.33) which exhibits a mesoscopic phase separation responsible for a field driven percolation, the glassy and short range ferromagnetic order observed here does not cause colossal magnetoresistance (CMR).Comment: accepted in Phys Rev

Aggregation-induced emission of [3]cumulenes functionalized with heptagon-containing polyphenylenes

This is accepted manuscript, the final published article is available in "García Jiménez, V.; et al. Aggregation-induced emission of [3]cumulenes functionalized with heptagon-containing polyphenylenes. Chemical Communications, online (2018). DOI: http://dx.doi.org/10.1039/C8CC00386FWe report the luminiscence at room temperature by aggregate formation of [3]cumulenes functionalized with propeller-like heptagon-containing polyphenylenes. These endgroups turn on the emission of a [3]cumulene by steric protection and restriction of their intramolecular rotations in the aggregates.European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (ERC-2015 -677023).Ministerio de Economía y Competitividad (MINECO, Spain – FEDER) (CTQ2015-70283-P, CTQ2014-53598-R, RyC-2013-12943).Fundação para a Ciência e a tecnologia (Portugal, IF/00759/2013, SFRH/BPD/75782/2011,SFRH/BPD/96707/2013,UID/NAN/50024/2013)

Evaluación del riesgo de deslizamientos superficiales para proyectos de infraestructura: caso de análisis en vereda El Cabuyal

In this paper an assessment of the hazard, the vulnerability and the risk associated with shallow landslides in a watershed of the Valle de Aburra is carried out. The TRIGRS model with a Monte Carlo simulation to estimate the probability of failure in the watershed using water table depth as the trigger factor is implemented, which allows the assessment of the hazard along with its annual probability of occurrence. Additionally, a quantitative model for physical vulnerability of structures which takes into account landslide intensity and resistance of exposed elements is used. The annual risk is estimated for a house of the study site as the product of the hazard and the damage costs due to the occurrence of the catastrophic event, which considers vulnerability. The methodology used focuses on the shallow landslide occurred on October 26, 2016 on a slope within the study site, which affected the house that is being analyzed.Este artículo presenta un análisis y evaluación cuantitativa de la amenaza, la vulnerabilidad y el riesgo asociados a deslizamientos superficiales en una subcuenca del Valle de Aburrá (Colombia). Se integra el modelo TRIGRS mediante una simulación de Montecarlo para la estimación de la probabilidad de falla en la subcuenca empleando una altura del nivel freático como factor desencadenante, que junto con su probabilidad de ocurrencia anual permiten la evaluación de la amenaza. Se emplea un modelo que cuantifica la vulnerabilidad física de estructuras basándose en la intensidad del deslizamiento y la resistencia del elemento expuesto. El riesgo anual se estima para una vivienda del sitio de estudio como el producto de la amenaza y el valor de la pérdida dado el evento catastrófico, considerando la vulnerabilidad. La metodología empleada se enfoca en el deslizamiento ocurrido el 26 de octubre de 2016 en un talud dentro del sitio de estudio que afectó la vivienda que es objeto de análisis

Identification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden markov models

Background: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. Results: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. Conclusions: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria

Aplicación web para el análisis de emociones y atención de estudiantes

Analyzing and monitoring students’ attention level in virtual environments allows teachers to take actions to improve teaching-learning processes. This study introduces the integration of two models, one for emotion recognition and one for attention analysis, both of them aimed at monitoring the interactions of students in virtual environments. Such integration was completed on a web platform employing the Flask framework, where the artificial intelligence models used to analyze the interaction can be executed. The results obtained show that teachers, as knowledge mediators, can use the platform to understand the behavior of the students in synchronous and asynchronous virtual environments and take actions to improve learning experiences. The results also highlight the advantages of employing the Model-View-Controller (MVC) pattern in web applications, using and integrating artificial intelligence techniques through the Flask framework.El análisis de emociones y el monitoreo del nivel de atención de los estudiantes en entornos virtuales permite a los docentes tomar acciones para mejorar los procesos de enseñanza-aprendizaje. Por esta razón, este trabajo presenta la integración de dos modelos: uno para el reconocimiento de emociones y otro para el análisis de atención, ambos con el objetivo de hacer monitoreo durante la interacción de un estudiante en entornos virtuales. Dicha integración se realiza en una plataforma web desarrollada en el entorno flask, en la que se pueden ejecutar los modelos de inteligencia artificial utilizados para la interacción. Los resultados obtenidos muestran que la plataforma podría ser utilizada por docentes como mediadores del conocimiento, para entender el comportamiento de los estudiantes en entornos virtuales tanto síncronos como asíncronos, y para tomar acciones que mejoren la experiencia de aprendizaje. Como ventaja adicional, los resultados aquí mostrados resaltan las ventajas que trae utilizar el Modelo Vista Controlador (MVC) en aplicaciones web, empleando e integrando técnicas de inteligencia artificial a través del framework Flask