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An enhanced database (RetroDB) of the Spanish wind energy resources, derived from a high spatial resolution integration with the WRF model, is proposed and evaluated. RetroDB provides hourly capacity factor (CF) values for the Spanish regions, along the period of 2007–2020, with an unprecedented spatial resolution. RetroDB estimates were benchmarked based on the ERA5 global reanalysis. A comprehensive evaluation study of both RetroDB and ERA5 estimates was conducted using surface and tall mast measurements, along with actual CF values. The extent to which RetroDB and ERA5 reproduced the CF spatial variability, distribution, and ramp distribution were specifically addressed. The results showed no differences between the global and regional reanalysis performance regarding nationally aggregated wind energy estimates. Nevertheless, RetroDB clearly shows a superior performance reproducing the wind speeds’ and CFs’ spatial and temporal distributions. This was found to be related to the higher reliability of RetroDB reproducing the aloft winds in complex topographic areas. Overall, the results clearly indicate that, in areas such as the study region, where the wind resources are mostly associated with topographic enhancements, high spatial resolution regional reanalyses are preferable over relative coarse reanalyses (e.g., ERA5), particularly for wind energy integration studies. RetroDB database is made publicly available.

Type 1 diabetes mellitus (T1DM) is characterized by beta cell loss because of an autoimmune attack. Here the authors show that an agonist for LRH-1/NR5A2, a nuclear receptor known to be protective against beta cell apoptosis, inhibits immune-mediated inflammation and hyperglycemia in T1DM mouse models.

With the recent advent of technology within the smart grid, many conventional concepts of power systems have undergone drastic changes. Owing to technological developments, even small customers can monitor their energy consumption and schedule household applications with the utilization of smart meters and mobile devices. In this paper, we address the power set-point tracking problem for an aggregator that participates in a real-time ancillary program. Fast communication of data and control signal is possible, and the end-user side can exploit the provided signals through demand response programs benefiting both customers and the power grid. However, the existing optimization approaches rely on heavy computation and future parameter predictions, making them ineffective regarding real-time decision-making. As an alternative to the fixed control rules and offline optimization models, we propose the use of an online optimization decision-making framework for the power set-point tracking problem. For the introduced decision-making framework, two types of online algorithms are investigated with and without projections. The former is based on the standard online gradient descent (OGD) algorithm, while the latter is based on the Online Frank–Wolfe (OFW) algorithm. The results demonstrated that both algorithms could achieve sub-linear regret where the OGD approach reached approximately 2.4-times lower average losses. However, the OFW-based demand response algorithm performed up to twenty-nine percent faster when the number of loads increased for each round of optimization.

This work presents an optimization framework based on mixed-integer programming techniques for a smart home’s optimal energy management. In particular, through a cost-minimization objective function, the developed approach determines the optimal day-ahead energy scheduling of all load types that can be either inelastic or can take part in demand response programs and the charging/discharging programs of an electric vehicle and energy storage. The underlying energy system can also interact with the power grid, exchanging electricity through sales and purchases. The smart home’s energy system also incorporates renewable energy sources in the form of wind and solar power, which generate electrical energy that can be either directly consumed for the home’s requirements, directed to the batteries for charging needs (storage, electric vehicles), or sold back to the power grid for acquiring revenues. Three short-term forecasting processes are implemented for real-time prices, photovoltaics, and wind generation. The forecasting model is built on the hybrid combination of the K-medoids algorithm and Elman neural network. K-medoids performs clustering of the training set and is used for input selection. The forecasting is held via the neural network. The results indicate that different renewables’ availability highly influences the optimal demand allocation, renewables-based energy allocation, and the charging–discharging cycle of the energy storage and electric vehicle.

Currently available treatments for secondary progressive multiple sclerosis(SPMS) have limited efficacy and/or safety concerns. Adipose-mesenchymal derived stem cells(AdMSCs) represent a promising option and can be readily obtained using minimally invasive procedures.In this triple-blind, placebo-controlled study, cell samples were obtained from consenting patients by lipectomy and subsequently expanded. Patients were randomized to a single infusion of placebo, low-dose(1x106cells/kg) or high-dose(4x106cells/kg) autologous AdMSC product and followed for 12 months. Safety was monitored recording adverse events, laboratory parameters, vital signs and spirometry. Expanded disability status score (EDSS), magnetic-resonance-imaging, and other measures of possible treatment effects were also recorded.Thirty-four patients underwent lipectomy for AdMSCs collection, were randomized and thirty were infused (11 placebo, 10 low-dose and 9 high-dose); 4 randomized patients were not infused because of karyotype abnormalities in the cell product. Only one serious adverse event was observed in the treatment arms (urinary infection, considered not related to study treatment). No other safety parameters showed changes. Measures of treatment effect showed an inconclusive trend of efficacy.Infusion of autologous AdMSCs is safe and feasible in patients with SPMS. Larger studies and probably treatment at earlier phases would be needed to investigate the potential therapeutic benefit of this technique.

Progress in the field of biocompatible SERS nanoparticles has promising prospects for biomedical applications. In this work, we have developed a biocompatible Raman probe by combining anisotropic silver nanoparticles with the dye rhodamine 6G followed by subsequent coating with bovine serum albumin. This nanosystem presents strong SERS capabilities in the near infrared (NIR) with a very high (2.7 × 107) analytical enhancement factor. Theoretical calculations reveal the effects of the electromagnetic and chemical mechanisms in the observed SERS effect for this nanosystem. Finite element method (FEM) calculations showed a considerable near field enhancement in NIR. Using density functional quantum chemical calculations, the chemical enhancement mechanism of rhodamine 6G by interaction with the nanoparticles was probed, allowing us to calculate spectra that closely reproduce the experimental results. The nanosystem was tested in cell culture experiments, showing cell internalization and also proving to be completely biocompatible, as no cell death was observed. Using a NIR laser, SERS signals could be detected even from inside cells, proving the applicability of this nanosystem as a biocompatible SERS probe.

Con el fin de obtener medidas angulares con el mínimo error y desviación posible se establece la fusión sensorial mediante el uso del Filtro de Kalman de las señales del acelerómetro y el giroscopio para un sistema en reposo sometido a perturbaciones (vibraciones). Finalmente el algoritmo es implementado en una plataforma que se basa en un microcontrolador dsPIC30F4011 que permite medir ángulos de inclinación en cabeceo y alabeo. Además en este documento se presenta una metodología que permite entender el manejo de los sensores inerciales (acelerómetro y giroscopio), así como también se da a conocer sus principales características y los problemas inherentes a su funcionamiento. Abstract:In order to obtain the minimum error and deviation of an angular measurement, is established sensory fusion using the Kalman Filter between the accelerometer and the gyroscope signals for a stationary system under disturbances (vibrations).Finally, the algorithm is implemented on a platform that is based on a microcontroller dsPIC30F4011 to measure angles in roll and pitch. Additionally, this paper presents a methodology that enables a better understanding of the management of inertial sensors (accelerometer and gyroscope) and also discloses its main characteristics and problems inherent in their operation.

En el presente documento se presenta el desarrollo e implementación en MATLAB de un algoritmo de SLAM para un robot móvil comercial, operando en entornos estructurados estáticos, cuya localización está dada por la odometría del robot y el modelo del mismo. Para la realización del mapeo se utiliza el sensor de rango laser Hokuyo URG-04LX; una vez obtenido el mapa se implementa un algoritmo capaz de detectar esquinas dentro del entorno, con el fin de que puedan ser utilizadas en futuras aplicaciones de SLAM donde sea necesario la inclusión de “landmarks” o características de entorno. Para atenuar los errores en posicionamiento inherentes a la odometría propia del robot se implementa un Filtro Extendido de Kalman entre la odometría y el modelo omnidireccional del robot móvil, en base a lo cual se obtienen mejores resultados para la localización. La detección de esquinas se realiza usando la Transformada de Hough, algoritmo mediante el cual se identifica líneas presentes en el mapa y posteriormente se halla esquinas como un cruce entre dos líneas. Se presentan los resultados como un análisis de los mapas obtenidos contrastados con los entornos reales, además del análisis de errores sobre la localización del robot. This paper presents the development and implementation of a Simultaneous Localization And Mapping (SLAM) algorithm for a commercial mobile robot, operating in structured and static environments. The location is given by the odometry of the robot and its model. To perform the mapping a sensor laser range Hokuyo URG - 04LX is used.Later, an algorithm capable of detecting corners in the environment is implemented, they can be used in future applications of SLAM where being necessary the inclusion of landmarks or characteristics of environment. To mitigate the position errors inherent to odometryof the robot is implemented an Extended Kalman Filter between the odometry and omnidirectional mobile robot model. This technique improves the results of localization. Corner's detection is performed using the Hough transform algorithm, which identifies lines on the map and subsequently corners like a cross between two lines. We present the results as an analysis of the obtained maps that include contrasts with the real environments. In addition,we analyze the location error of the robot.

En el presente documento se implementa un sistema electro-óptico, el mismo que posee un algoritmo que permite estabilizar una plataforma con dos grados de libertad ante perturbaciones y realizar apuntamiento hacia una dirección, especificada mediante latitud y longitud, a través de “Google Earth”. Este sistema, se encuentra constituido por una plataforma con movimientos en el eje vertical (cabeceo) y horizontal (guiñada). Además, dispone de una cámara de espectro visible, una cámara térmica y una cámara de medición láser para adquirir imágenes y tomar medidas de distancias. Abstract: In this document, we implement an electro-optical system, which one has an algorithm to stabilize a platform with two degrees of freedom against disturbances and perform pointing in one direction, specified by latitude and longitude in “Google Earth”. This system is constituted by a platform that moves in the vertical axis (pitch) and horizontal axis (yaw). It also has a visible spectrum camera, a thermal camera and laser rangefinder to acquire images and take measurements of distances.

The concept of a European super-grid for electricity presents clear advantages for a reliable and affordable renewable power production (photovoltaics and wind). Based on the mean-variance portfolio optimization analysis, we explore optimal scenarios for the allocation of new renewable capacity at national level in order to provide to energy decision-makers guidance about which regions should be mostly targeted to either maximize total production or reduce its day-to-day variability. The results show that the existing distribution of renewable generation capacity across Europe is far from optimal: i.e. a ‘better’ spatial distribution of resources could have been achieved with either a ~31% increase in mean power supply (for the same level of day-to-day variability) or a ~37.5% reduction in day-to-day variability (for the same level of mean productivity). Careful planning of additional increments in renewable capacity at the European level could, however, act to significantly ameliorate this deficiency. The choice of where to deploy resources depends, however, on the objective being pursued—if the goal is to maximize average output, then new capacity is best allocated in the countries with highest resources, whereas investment in additional capacity in a north/south dipole pattern across Europe would act to most reduce daily variations and thus decrease the day-to-day volatility of renewable power supply.

In recent years, it has become accepted that α-synuclein (αSyn) has a key role in the microglia-mediated neuroinflammation, which accompanies the development of Parkinson's disease and other related disorders, such as Dementia with Lewy Bodies and Alzheimer's disease. Nevertheless, the cellular and molecular mechanisms underlying its pathological actions, especially in the sporadic forms of the diseases, are not completely understood. Intriguingly, several epidemiological and animal model studies have revealed a link between certain microbial infections and the onset or progression of sporadic forms of these neurodegenerative disorders. In this work, we have characterized the effect of toll-like receptor (TLR) stimulation on primary murine microglial cultures and analysed the impact of priming cells with extracellular wild-type (Wt) αSyn on the subsequent TLR stimulation of cells with a set of TLR ligands. By assaying key interleukins and chemokines we report that specific stimuli, in particular Pam3Csk4 (Pam3) and single-stranded RNA40 (ssRNA), can differentially affect the TLR2/1- and TLR7-mediated responses of microglia when pre-conditioned with αSyn by augmenting IL-6, MCP-1/CCL2 or IP-10/CXCL10 secretion levels. Furthermore, we report a skewing of αSyn-primed microglia stimulated with ssRNA (TLR7) or Pam3 (TLR2/1) towards intermediate but at the same time differential, M1/M2 phenotypes. Finally, we show that the levels and intracellular location of activated caspase-3 protein change significantly in αSyn-primed microglia after stimulation with these particular TLR agonists. Overall, we report a remarkable impact of non-aggregated αSyn pre-sensitization of microglia on TLR-mediated immunity, a phenomenon that could contribute to triggering the onset of sporadic α-synuclein-related neuropathologies.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized pathologically by the presence in the brain of intracellular protein inclusions highly enriched in aggregated alpha-synuclein (α-Syn). Although it has been established that progression of the disease is accompanied by sustained activation of microglia, the underlying molecules and factors involved in these immune-triggered mechanisms remain largely unexplored. Lately, accumulating evidence has shown the presence of extracellular α-Syn both in its aggregated and monomeric forms in cerebrospinal fluid and blood plasma. However, the effect of extracellular α-Syn on cellular activation and immune mediators, as well as the impact of familial PD-linked α-Syn mutants on this stimulation, are still largely unknown.In this work, we have compared the activation profiles of non-aggregated, extracellular wild-type and PD-linked mutant α-Syn variants on primary glial and microglial cell cultures. After stimulation of cells with α-Syn, we measured the release of Th1- and Th2- type cytokines as well as IP-10/CXCL10, RANTES/CCL5, MCP-1/CCL2 and MIP-1α/CCL3 chemokines. Contrary to what had been observed using cell lines or for the case of aggregated α-Syn, we found strong differences in the immune response generated by wild-type α-Syn and the familial PD mutants (A30P, E46K and A53T).These findings might contribute to explain the differences in the onset and progression of this highly debilitating disease, which could be of value in the development of rational approaches towards effective control of immune responses that are associated with PD.

Resumen:En el presente documento se desarrolla el diseño y construcción de tres minirobots,losmismos que se desplazan a través de un laberinto de superficie regular; evitando colisiones y reconociendo rutas, con el fin de realizar el mapeodel laberinto en menor tiempo comparado con el que tardaría un solo robot. Cada mini-robot recoge datos de la exploración realizada y los envía a un dispositivo coordinador (computador). Los datos son procesados usando MATLAB por medio de una interfaz gráfica donde se visualiza las rutas recorridas y la exploración de su entorno de una forma aproximada. Como resultado más sobresaliente se obtiene la ruta más corta de un laberinto, mediante un proceso de eliminación de aquellas que no son válidas hacia la salida. Abstract: This paper develops the design and construction of three mini-robots, which move through a maze of regular surface; avoiding collisions and recognizing routes, in order to perform the mapping of the maze in less time compared to what would take a single robot. Each mini-robot collects data from scanning and sends a coordinator device (computer). All data were processed using MATLAB via a graphical interface where the routes traveled and exploring their environment in an approximate manner is displayed. The most outstanding result of the shortest path maze is obtained by a process of elimination of those that are not valid for the exit.