Contrastación de diferentes criterios numéricos para la resolución de flujos potenciales mediante el empleo de coordenadas curvilíneas. Parte I: Función de corriente

En este trabajo se analizan y contrastan diferentes criterios numéricos para la resolución de flujos potenciales subsónicos compresibles mediante el empleo de la función de corriente. Los dominios son discretizados en base a la generación de coordenadas curvilíneas adaptables a los contornos. Las ecuaciones de discretización son obtenidas a partir de la ecuación diferencial de la función de corriente, o bien de efectuar balances sobre volúmenes de control finitos asignados a los nodos de la malla. A modo de ejemplo y para el estudio numérico se analizan dos situaciones concretas de flujos confinados; los resultados presentados ponen de manifiesto la influencia del tipo de malla generada y de los criterios numéricos utilizados en la discretización de las ecuaciones.Peer Reviewe

Estrogen influences cocaine-induced blood oxygen level-dependent signal changes in female rats

We investigated the effect of estrogen on cocaine-induced brain activity using blood oxygen level-dependent (BOLD) magnetic resonance imaging. Ovariectomized (Ovx) rats without estrogen and Ovx rats with estrogen (Ovx+E) were given a single saline or cocaine injection (15 mg/kg, i.p.) for 5 d. After 7 d of withdrawal from injections, rats were challenged with cocaine during functional imaging. Acute cocaine administration produced positive BOLD activation in the prefrontal cortex, nucleus accumbens, striatum, ventral tegmental area, and hippocampus, among other brain regions. Positive BOLD signal changes were lower in Ovx+E than in Ovx rats. With repeated cocaine administration, Ovx+E rats showed enhanced BOLD signal changes in the nucleus accumbens, ventral tegmental area, and hippocampus compared with acutely treated animals. Our results indicate that estrogen influences the effects of acute and repeated cocaine administration on BOLD signal changes. The data suggest that in females with estrogen, cocaine-induced neuronal activity is enhanced after repeated cocaine administration. It is possible that the actions of estrogen within the aforementioned brain regions potentiate the behavioral response to cocaine observed in female rats

Farming and earth observation: sentinel-2 data to estimate within-field wheat grain yield

Wheat grain yield (GY) is a crop feature of central importance affecting agricultural, environmental, and socioeconomic sustainability worldwide. Hence, the estimation of within-field variability of GY is pivotal for the agricultural management, especially in the current global change context. In this sense, Earth Observation Systems (EOS) are key technologies that use satellite data to monitor crop yield, which can guide the application of precision farming. Yet, novel research is required to improve the multiplatform integration of data, including data processing, and the application of this discipline in agricultural management. This article provides a novel methodological analysis and assessment of its applications in precision farming. It presents an integration of wheat GY, Global Positioning Systems (GPS), combine harvester data, and EOS Sentinel-2 multispectral bands. Moreover, it compares several indices and machine learning (ML) approaches to map within-field wheat GY. It also analyses the importance of multi-date remote sensing imagery and explores its potential applications in precision agriculture. The study was conducted in Spain, a major European wheat producer. Within-field GY data was obtained from a GPS combine harvester machine for 8 fields over three seasons (2017-2019) and consecutively processed to match Sentinel-2 10 m pixel size. Seven vegetation indices (NDVI, GNDVI, EVI, RVI, TGI, CVI and NGRDI) as well as the biophysical parameter LAI (leaf area index) retrieved with radiative transfer models (RTM) were calculated from Sentinel-2 bands. Sentinel-2 10 m resolution bands alone were also used as variables. Random forest, support vector machine and boosted regressions were used as modelling approaches, and multilinear regression was calculated as baseline. Different combinations of dates of measurement were tested to find the most suitable model feeding data. LAI retrieved from RTM had a slightly improved performance in estimating within-field GY in comparison with vegetation indices or Sentinel-2 bands alone. At validation, the use of multi-date Sentinel-2 data was found to be the most suitable in comparison with single date images. Thus, the model developed with random forest regression (e.g. R-2 = 0.89, and RSME = 0.74 t/ha when using LAI) outperformed support vector machine (R-2 = 0.84 and RSME = 0.92 t/ha), boosting regression (R-2 = 0.85 and RSME = 0.88 t/ha) and multilinear regression (R-2 = 0.69 and RSME = 1.29 t/ha). However, single date images at specific phenological stages (e.g. R-2 = 0.84, and RSME = 0.88 t/ha using random forest at stem elongation) also posed relatively high R-2 and low RMSE, with potential for precision farming management before harvest.A & nbsp;We acknowledge the support of the project PID2019-106650RB-C21 from the Ministerio de Ciencia e Innovacion, Spain. J.S. is a recipient of a FPI doctoral fellowship from the same institution (grant: PRE2020-091907) . J.L.A. acknowledges support from the Institucio Catalana de Recerca i Estudis Avancats (ICREA) , Generalitat de Catalunya, Spain) . S. C.K. is supported by the Ramon y Cajal RYC-2019-027818-I research fellowship from the Ministerio de Ciencia e Innovacion, Spain. We acknowledge the support of Cerealto Siro Group, together with Cristina de Diego and Javier Velasco, technical staff from the company, by providing the wheat yield data. This research was also supported by the COST Action CA17134 SENSECO (Optical synergies for spatiotemporal sensing of scalable ecophysiological traits) funded by COST (European Cooperation in Science and Technology, www.cost.eu)

Seed germination and seedling allogamy in Rosmarinus officinalis: the costs of inbreeding

1) Self-pollination by geitonogamy is likely in self-compatible plants that simultaneously expose large numbers of flowers to pollinators. However, the progeny of these plants is often highly allogamous. Although mechanisms to increase cross-pollination have been identified and studied, their relative importance has rarely been addressed simultaneously in plant populations. (2) We used Rosmarinus officinalis to explore the factors that influence the probability of self-fertilization due to geitonogamy or that purge its consequences, focusing on their effect on seed germination and allogamy rate. For doing this, we experimentally tested the effects of geitonogamy on the proportion of filled seeds and how it influences germination rates. Then during two field seasons, we studied how life-history and flowering traits of individuals influence seed germination and allogamy rates of their progeny in wild populations at the extremes of the altitudinal range. The traits considered were plant size, population density, duration of the flowering season, number of open flowers, flowering synchrony among individuals within populations, and the proportion of male-sterile flowers. (3) We found that most seeds obtained experimentally from self-pollinations were apparently healthy but in fact empty, and that the presence of filled seeds drove the differences in germination rates between self- and cross-pollination experiments. Plants from wild populations consistently showed low germination rates and high rates of allogamy as determined with microsatellites. Germination rates related positively to the length of the flowering season, flowering synchrony and the rate of male-sterile flowers whereas the rate of allogamous seedlings was positively related only to the rate of male-sterile flowers. (4) Rosemary plants purge most of the inbreeding caused by its pollination system by aborting seeds. This study showed that the rates of seed germination and of the resulting allogamy are a function of a complex combination of factors that vary in space and time. Male sterility of flowers, length of the flowering season and flowering synchrony of individuals within populations all favor high rates of cross-pollination, therefore increasing germination and allogamy rates. These flowering traits appear to be highly plastic and respond to local and seasonal environmental conditions

Remote Sensing for Precision Agriculture: Sentinel-2 Improved Features and Applications

The use of satellites to monitor crops and support their management is gathering increasing attention. The improved temporal, spatial, and spectral resolution of the European Space Agency (ESA) launched Sentinel-2 A + B twin platform is paving the way to their popularization in precision agriculture. Besides the Sentinel-2 A + B constellation technical features the open-access nature of the information they generate, and the available support software are a significant improvement for agricultural monitoring. This paper was motivated by the challenges faced by researchers and agrarian institutions entering this field; it aims to frame remote sensing principles and Sentinel-2 applications in agriculture. Thus, we reviewed the features and uses of Sentinel-2 in precision agriculture, including abiotic and biotic stress detection, and agricultural management. We also compared the panoply of satellites currently in use for land remote sensing that are relevant for agriculture to the Sentinel-2 A + B constellation features. Contrasted with previous satellite image systems, the Sentinel-2 A + B twin platform has dramatically increased the capabilities for agricultural monitoring and crop management worldwide. Regarding crop stress monitoring, Sentinel-2 capacities for abiotic and biotic stresses detection represent a great step forward in many ways though not without its limitations; therefore, combinations of field data and different remote sensing techniques may still be needed. We conclude that Sentinel-2 has a wide range of useful applications in agriculture, yet still with room for further improvements. Current and future ways that Sentinel-2 can be utilized are also discussed.This research was funded by the Spanish projects AGL2016-76527-R and IRUEC PCIN-2017-063 from the Ministerio de Economía y Competividad (MINECO, Spain) and by the support of Catalan Institution for Research and Advanced Studies (ICREA, Generalitat de Catalunya, Spain), through the ICREA Academia Program

Probabilistic load forecasting for building energy models

In the current energy context of intelligent buildings and smart grids, the use of load forecasting to predict future building energy performance is becoming increasingly relevant. The prediction accuracy is directly influenced by input uncertainties such as the weather forecast, and its impact must be considered. Traditional load forecasting provides a single expected value for the predicted load and cannot properly incorporate the effect of these uncertainties. This research presents a methodology that calculates the probabilistic load forecast while accounting for the inherent uncertainty in forecast weather data. In the recent years, the probabilistic load forecasting approach has increased in importance in the literature but it is mostly focused on black-box models which do not allow performance evaluation of specific components of envelope, HVAC systems, etc. This research fills this gap using a white-box model, a building energy model (BEM) developed in EnergyPlus, to provide the probabilistic load forecast. Through a Gaussian kernel density estimation (KDE), the procedure converts the point load forecast provided by the BEM into a probabilistic load forecast based on historical data, which is provided by the building’s indoor and outdoor monitoring system. An hourly map of the uncertainty of the load forecast due to the weather forecast is generated with different prediction intervals. The map provides an overview of different prediction intervals for each hour, along with the probability that the load forecast error is less than a certain value. This map can then be applied to the forecast load that is provided by the BEM by applying the prediction intervals with their associated probabilities to its outputs. The methodology was implemented and evaluated in a real school building in Denmark. The results show that the percentage of the real values that are covered by the prediction intervals for the testing month is greater than the confidence level (80%), even when a small amount of data are used for the creation of the uncertainty map; therefore, the proposed method is appropriate for predicting the probabilistic expected error in load forecasting due to the use of weather forecast data

Energy efficiency of ventilated façades with near infrared range reflective ceramic tiles

La creciente concienciación social respecto a la construcción sostenible y el ahorro energético en edificios está conduciendo a prescriptores y usuarios finales a tomar en consideración nuevas soluciones constructivas. Sin embargo, su introducción en el mercado es lenta y difícil, debido tanto a las limitaciones de las herramientas reconocidas de simulación térmica, que no permiten efectuar estimaciones integrando sistemas innovadores, como a la dificultad para validar su eficiencia en edificios reales previamente a su comercialización. En el presente trabajo se analiza la eficiencia energética de una fachada ventilada resuelta con baldosas cerámicas reflectantes al infrarrojo cercano, mediante la integración en el programa EnergyPlus de un modelo matemático que ha sido validado en el edificio experimental CIES Living Lab de Castellón.The growing social awareness with regard to sustainable construction and energy efficiency in buildings is leading specifications writers and end users to take into account new construction solutions. However, the introduction of these construction solutions into the market is slow and difficult owing to the limitations of the recognised thermal simulation tools, which do not allow estimations to be made when integrating innovative systems, and to the difficulty of validating their efficiency in actual buildings before marketing them. The present study analyses the energy efficiency of a ventilated façade made up of near-infrared reflective ceramic tiles, by integrating a mathematical model validated in the CIES Living Lab experimental building in Castellón into the EnergyPlus program.Este estudio ha sido cofinanciado por la plataforma Climate- KIC en el marco del proyecto Building Technologies Accelerator (BTA)