A novel approach to statistical-dynamical downscaling for long-term wind resource predictions

A novel method to determine representative periods (typically a year) for the estimation of the longterm mesoscale wind resource has been proposed and compared to other recently published techniques. It provides a computationally lean while accurate solution of the problem of constructing long-term mesoscale wind maps through downscaling without having to go through a brute force procedure. Applications include a wider dissemination of mesoscale wind maps because of faster and cheaper execution, as well as greater flexibility for sensitivity analyses

Long-term wind resource assessment for small and medium-scale turbines using operational forecast data and measure-correlate-predict

Output from a state-of-the-art, 4 km resolution, operational forecast model (UK4) was investigated as a source of long-term historical reference data for wind resource assessment. The data were used to implement measure-correlate-predict (MCP) approaches at 37 sites throughout the United Kingdom (UK). The monthly and hourly linear correlation between the UK4-predicted and observed wind speeds indicates that UK4 is capable of representing the wind climate better than the nearby meteorological stations considered. Linear MCP algorithms were implemented at the same sites using reference data from UK4 and nearby meteorological stations to predict the long-term (10-year) wind resource. To obtain robust error statistics, MCP algorithms were applied using onsite measurement periods of 1-12 months initiated at 120 different starting months throughout an 11 year data record. Using linear regression MCP over 12 months, the average percentage errors in the long-term predicted mean wind speed and power density were 3.0% and 7.6% respectively, using UK4, and 2.8% and 7.9% respectively, using nearby meteorological stations. The results indicate that UK4 is highly competitive with nearby meteorological observations as an MCP reference data source. UK4 was also shown to systematically improve MCP predictions at coastal sites due to better representation of local diurnal effects

The membrane-spanning 4-domains, subfamily A (MS4A) gene cluster contains a common variant associated with Alzheimer's disease

Background\ud In order to identify novel loci associated with Alzheimer's disease (AD), we conducted a genome-wide association study (GWAS) in the Spanish population.\ud \ud Methods\ud We genotyped 1,128 individuals using the Affymetrix Nsp I 250K chip. A sample of 327 sporadic AD patients and 801 controls with unknown cognitive status from the Spanish general population were included in our initial study. To increase the power of the study, we combined our results with those of four other public GWAS datasets by applying identical quality control filters and the same imputation methods, which were then analyzed with a global meta-GWAS. A replication sample with 2,200 sporadic AD patients and 2,301 controls was genotyped to confirm our GWAS findings.\ud \ud Results\ud Meta-analysis of our data and independent replication datasets allowed us to confirm a novel genome-wide significant association of AD with the membrane-spanning 4-domains subfamily A (MS4A) gene cluster (rs1562990, P = 4.40E-11, odds ratio = 0.88, 95% confidence interval 0.85 to 0.91, n = 10,181 cases and 14,341 controls).\ud \ud Conclusions\ud Our results underscore the importance of international efforts combining GWAS datasets to isolate genetic loci for complex diseases

Comparison between the bivariate Weibull probability approach and linear regression for assessment of the long-term wind energy resource using MCP

A detailed investigation of a measure-correlate-predict (MCP) approach based on the bivariate Weibull (BW) probability distribution of wind speeds at pairs of correlated sites has been conducted. Since wind speeds are typically assumed to follow Weibull distributions, this approach has a stronger theoretical basis than widely used regression MCP techniques. Building on previous work that applied the technique to artificially generated wind data, we have used long-term (11 year) wind observations at 22 pairs of correlated UK sites. Additionally, 22 artificial wind data sets were generated from ideal BW distributions modelled on the observed data at the 22 site pairs. Comparison of the fitting efficiency revealed that significantly longer data periods were required to accurately extract the BW distribution parameters from the observed data, compared to artificial wind data, due to seasonal variations. The overall performance of the BW approach was compared to standard regression MCP techniques for the prediction of the 10 year wind resource using both observed and artificially generated wind data at the 22 site pairs for multiple short-term measurement periods of 1-12 months. Prediction errors were quantified by comparing the predicted and observed values of mean wind speed, mean wind power density, Weibull shape factor and standard deviation of wind speeds at each site. Using the artificial wind data, the BW approach outperformed the regression approaches for all measurement periods. When applied to the real wind speed observations however, the performance of the BW approach was comparable to the regression approaches when using a full 12 month measurement period and generally worse than the regression approaches for shorter data periods. This suggests that real wind observations at correlated sites may differ from ideal BW distributions and hence regression approaches, which require less fitting parameters, may be more appropriate, particularly when using short measurement periods

Guía de actuación en anafilaxia en Latinoamérica. Galaxia-Latam

Anaphylaxis is a severe allergic reaction with a rapid onset and it is potentially life-threatening. Its clinical manifestations are varied; they may affect the skin, the cardiovascular system, the respiratory system, and the digestive system, among others. The treatment of choice, which is an intra-muscular injection of epinephrine (adrenaline), must be applied promptly. Therefore, being prepared to recognize it properly is of crucial importance. The objective of this clinical practice guide is to improve the knowledge of health professionals about anaphylaxis and, consequently, to optimize the treatment and long-term management of this reaction. This guide is adapted to the peculiarities of Latin America; especially in matters regarding the treatment. The need to introduce epinephrine auto-injectors in countries that don't have them yet is highlighted

Assessment of the capacity credit of wind power in Mexico

A comprehensive assessment of the capacity credit of potential wind power developments in Mexico has been conducted for the first time. The analysis is based on an 80 m wind speed map generated from the North American Regional Reanalysis (NARR) data base and a set of restrictions, including proximity to transmission lines and major roads. Potential wind farm sites complying with all restrictions were populated with wind farms according to different scenarios; consecutive deployment of wind power from 1% to 15% system penetration was considered in all cases. In a set of one-region scenarios the evolution of the capacity credit was studied for different levels of intra-regional diversification. Near-generic decay according to a power law was observed at high penetration levels, whereas a notorious benefit was obtained from diversification at low and intermediate wind power penetration. In order to assess the potential benefits of inter-regional diversification, an optimization procedure was conducted. A significant improvement of the capacity credit decay curve was obtained for all levels of penetration. Optimal sets are characterized by a balanced utilization among regions with a relative insensitivity with respect to the exact composition of the wind farm set. The results are believed to be useful for the expansion planning of the Mexican electric gri