Sport as a privilege in Spain

The reduction of Physical Education hours in the Spanish curriculum originates from a false premise: families are already aware of the importance of physical activity, and attempt to compensate for the lack of it at school with an extra schedule. It seems then, that there is an assumption that classes that are available after school are only related to physical activity: this is not the case. Furthermore, only those families that are fully aware of the consequences of their children’s inactivity, and who can (and want to) invest in those extra classes and engage in some kind of physical activity after school. But the reality is that Physical activity only is important for some families

Exploration of flowering control in Lolium perenne L.

End of project reportFlowering or heading in Lolium perenne (perennial ryegrass) is induced by a period of vernalization, followed by long days at higher temperatures. When heading occurs there is a reduction in the feed quality of the forage and therefore extending the period of vegetative growth or eliminating heading during the growing season will improve the potential of perennial ryegrass in agriculture. Conversely, a better control of flowering time and increased heading will lead to higher seed yield for commercial producers. The aim of this project was to investigate the underlying genetic control of flowering time in perennial ryegrass. An F1 population was created by crosspollinating two lines with different heading dates and a genetic linkage map was constructed using Simple Sequence Repeat (SSR) markers. The population and genetic linkage map was then used to identify Quantitative Trait Loci (QTL) associated with heading date, spike length and spikelets per spike. A number of QTL were identified for all traits, some of which had not previously been identified in perennial ryegrass. A Suppression Subtractive Hybridization (SSH) study was also employed to identify genes differentially expressed between an extremely late flowering line and earlier flowering sibling line. Expression analysis of a number of identified genes through floral induction was performed using real time RT-PCR. This revealed a number of transcripts with expression profiles indicative of a role to play in floral induction

Airborne LiDAR and high resolution satellite data for rapid 3D feature extraction

This work uses the canopy height model (CHM) based workflow for individual tree crown delineation and 3D feature extraction approach (Overwatch Geospatial's proprietary algorithm) for building feature delineation from high-density light detection and ranging (LiDAR) point cloud data in an urban environment and evaluates its accuracy by using very high-resolution panchromatic (PAN) (spatial) and 8-band (multispectral) WorldView-2 (WV-2) imagery. LiDAR point cloud data over San Francisco, California, USA, recorded in June 2010, was used to detect tree and building features by classifying point elevation values. The workflow employed includes resampling of LiDAR point cloud to generate a raster surface or digital terrain model (DTM), generation of a hill-shade image and an intensity image, extraction of digital surface model, generation of bare earth digital elevation model (DEM) and extraction of tree and building features. First, the optical WV-2 data and the LiDAR intensity image were co-registered using ground control points (GCPs). The WV-2 rational polynomial coefficients model (RPC) was executed in ERDAS Leica Photogrammetry Suite (LPS) using supplementary?.RPB file. In the second stage, ortho-rectification was carried out using ERDAS LPS by incorporating well-distributed GCPs. The root mean square error (RMSE) for the WV-2 was estimated to be 0.25 m by using more than 10 well-distributed GCPs. In the second stage, we generated the bare earth DEM from LiDAR point cloud data. In most of the cases, bare earth DEM does not represent true ground elevation. Hence, the model was edited to get the most accurate DEM/ DTM possible and normalized the LiDAR point cloud data based on DTM in order to reduce the effect of undulating terrain. We normalized the vegetation point cloud values by subtracting the ground points (DEM) from the LiDAR point cloud. A normalized digital surface model (nDSM) or CHM was calculated from the LiDAR data by subtracting the DEM from the DSM. The CHM or the normalized DSM represents the absolute height of all aboveground urban features relative to the ground. After normalization, the elevation value of a point indicates the height from the ground to the point. The above-ground points were used for tree feature and building footprint extraction. In individual tree extraction, first and last return point clouds were used along with the bare earth and building footprint models discussed above. In this study, scene dependent extraction criteria were employed to improve the 3D feature extraction process. LiDAR-based refining/ filtering techniques used for bare earth layer extraction were crucial for improving the subsequent 3D features (tree and building) feature extraction. The PAN-sharpened WV-2 image (with 0.5 m spatial resolution) was used to assess the accuracy of LiDAR-based 3D feature extraction. Our analysis provided an accuracy of 98% for tree feature extraction and 96% for building feature extraction from LiDAR data. This study could extract total of 15143 tree features using CHM method, out of which total of 14841 were visually interpreted on PAN-sharpened WV-2 image data. The extracted tree features included both shadowed (total 13830) and non-shadowed (total 1011). We note that CHM method could overestimate total of 302 tree features, which were not observed on the WV-2 image. One of the potential sources for tree feature overestimation was observed in case of those tree features which were adjacent to buildings. In case of building feature extraction, the algorithm could extract total of 6117 building features which were interpreted on WV-2 image, even capturing buildings under the trees (total 605) and buildings under shadow (total 112). Overestimation of tree and building features was observed to be limiting factor in 3D feature extraction process. This is due to the incorrect filtering of point cloud in these areas. One of the potential sources of overestimation was the man-made structures, including skyscrapers and bridges, which were confounded and extracted as buildings. This can be attributed to low point density at building edges and on flat roofs or occlusions due to which LiDAR cannot give as much precise planimetric accuracy as photogrammetric techniques (in segmentation) and lack of optimum use of textural information as well as contextual information (especially at walls which are away from roof) in automatic extraction algorithm. In addition, there were no separate classes for bridges or the features lying inside the water and multiple water height levels were also not considered. Based on these inferences, we conclude that the LiDAR-based 3D feature extraction supplemented by high resolution satellite data is a potential application which can be used for understanding and characterization of urban setup

Enhanced urban landcover classification for operational change detection study using very high resolution remote sensing data

This study presents an operational case of advancements in urban land cover classification and change detection by using very high resolution spatial and multispectral information from 4-band QuickBird (QB) and 8-band WorldView-2 (WV-2) image sequence. Our study accentuates quantitative, pixel based, image difference approach for operational change detection using very high resolution pansharpened QB and WV-2 images captured over San Francisco city, California, USA (37° 44" 30N', 122° 31" 30' W and 37° 41" 30'N,122° 20" 30' W). In addition to standard QB image, we compiled three multiband images from eight pansharpened WV-2 bands: (1) multiband image from four traditional spectral bands, i.e., Blue, Green, Red and near-infrared 1 (NIR1) (henceforth referred as "QB equivalent WV-2"), (2) multiband image from four new spectral bands, i.e., Coastal, Yellow, Red Edge and NIR2 (henceforth referred as "new band WV-2"), and (3) multiband image consisting of four traditional and four new bands (henceforth referred as "standard WV-2"). All the four multiband images were classified using support vector machine (SVM) classifier into four most abundant land cover classes, viz, hard surface, vegetation, water and shadow. The assessment of classification accuracy was performed using random selection of 356 test points. Land cover classifications on "standard QB" image (kappa coeffiecient, κ = 0.93), "QB equivalent WV-2" image (κ = 0.97), and "new band WV-2" image (κ = 0.97) yielded overall accuracies of 96.31, 98.03 and 98.31, respectively, while "standard WV-2" image (κ = 0.99) yielded an improved overall accuracy of 99.18. It is concluded that the addition of four new spectral bands to the existing four traditional bands improved the discrimination of land cover targets, due to increase in the spectral characteristics of WV-2 satellite. Consequently, to test the validity of improvement in classification process for implementation in operational change detection application, comparative assessment of transition of various landcover classes in three WV-2 images with respect to "standard QB" image was carried out using image difference method. As far as waterbody class is concerned, there was no significant transition observed in all the three WorldView-2 Images, whereas, hard surface class showed lowest transition in "standard WV-2" image and highest in case of "new band WV-2". The most significant transition was occurred in vegetation class in all of the three images, showing positive change (increase) in standard WV-2 image (0.31 Sq. Km) and negative change (decrease) in other two images (-0.12 Sq. Km for "QB equivalent WV-2" image and -31.15 Sq. Km in "new band WV-2" image) with considerable amount. Similar case was observed with the shadow class, but the difference is, transition from shadow to other classes was negative in all the three WV-2 images which can be attributed to the fact that, "standard QB" image had more shadow area (based on acquisition time and sun position) than WV-2, that means all the band combinations of WV-2 succeeded in extracting the features hidden below the shadow in "standard QB" image. These trends indicate that the overall bandwise transition in landcover classes in case of "standard WV-2" is more precise than other two images. We note that "QB equivalent WV-2" image had narrower band widths than those of "standard QB" image but the observed vegetation change is not prominent as in case of other two images, but at the same time, transition in hard surface and waterbody was discerned more efficiently than "new band WV-2" image. The addition of new bands in WV-2 enabled more effective vegetation analysis, so the vegetation transition results shown by "new band WV-2" image were at par with the "standard WV-2" image, showing the importance of these newly added bands in the WV-2 imagery, with comparatively lower transitions in other classes. In a nutshell, it can be claimed that incorporation of new bands along with even narrower Red, Green, Blue and Near Infrared-1 bands in WV-2 image holds remarkable importance which leads to enhancement in the potential of WV-2 imagery in change detection and other feature extraction studies

Post-tsunami impact study on thermohaline structure in the Bay of Bengal

Temperature and salinity profiles measured on-board ORV Sagar Kanya, during 18 January-17 February 2005, in the vicinity of the Chennai coast and west of the Andaman (AN) Islands, have been employed to assess and quantify the post-tsunami impact on the upper-ocean thermohaline structure, by comparing these with previous year's data. In the vicinity of the AN Islands, the sea surface temperature increased by 0.5°C and surface salinity decreased from 33.5 to 32 psu, between 90°E and 92°E along 10°N. This freshening has been attributed to westward geostrophic flow from the AN Sea facilitated by a sea surface height gradient inferred from the merged multi-mission satellite data. Significant temperature variations exceeding 1°C were observed between 50 and 250 m, west of the AN Islands. Near the Chennai coast (10°N, 80.9°E), influx of freshwater from the northern Bay of Bengal reduced salinity by 0.8 psu and stratification in the upper 100 m was observed. Upward shift in the 20°C isotherm was observed at all locations, suggesting a vertical entrainment. In general, this study reveals that considerable thermohaline variability has occurred in the upper 300 m water column, which is expected to have a significant impact on primary production and fisheries

Matrix interpretation of multiple orthogonality

In this work we give an interpretation of a (s(d + 1) + 1)-term recurrence relation in terms of type II multiple orthogonal polynomials.We rewrite this recurrence relation in matrix form and we obtain a three-term recurrence relation for vector polynomials with matrix coefficients. We present a matrix interpretation of the type II multi-orthogonality conditions.We state a Favard type theorem and the expression for the resolvent function associated to the vector of linear functionals. Finally a reinterpretation of the type II Hermite- Padé approximation in matrix form is given

Minimal flavour violation extensions of the seesaw

We analyze the most natural formulations of the minimal lepton flavour violation hypothesis compatible with a type-I seesaw structure with three heavy singlet neutrinos N, and satisfying the requirement of being predictive, in the sense that all LFV effects can be expressed in terms of low energy observables. We find a new interesting realization based on the flavour group $SU(3)_e\times SU(3)_{\ell+N}$ (being $e$ and $\ell$ respectively the SU(2) singlet and doublet leptons). An intriguing feature of this realization is that, in the normal hierarchy scenario for neutrino masses, it allows for sizeable enhancements of $\mu \to e$ transitions with respect to LFV processes involving the $\tau$ lepton. We also discuss how the symmetries of the type-I seesaw allow for a strong suppression of the N mass scale with respect to the scale of lepton number breaking, without implying a similar suppression for possible mechanisms of N productionComment: 14 pages, 6 figure

Prevalence of sleep complaints in Colombia at different altitudes

AbstractStudy objectivesTo determine the prevalence of sleep complaints in adults in Colombia at different altitudes.DesignCross-sectional, population-based and observational study.SettingUrban areas in three cities (Bogotá, Bucaramanga, Santa Marta) located between 15 and 2640 masl. Subjects Over 18 years old.InterventionsEpworth sleepiness scale (ESS), Pittsburgh sleep quality index (PSQI), Berlin questionnaire, STOP-Bang questionnaire and diagnostic criteria for restless leg syndrome (IRLSSG).Measurements and resultsThe overall prevalence of sleep complaints was 59.6% (CI 95%: 57.3; 61.8%). According to the Pittsburgh scale, 45.3% (CI 95%: 43.0; 47.5) required medical assistance. The Berlin questionnaire indicated that 19.0% (CI 95%: 17.3; 20.8%) had a high risk of sleep apnea (OSA) compared to 26.9% (CI 95%: 24.9; 29.0%) according to STOP-Bang. Among the subjects, 13.7% (CI 95%: 12.3; 15.3%) had excessive daytime sleepiness and 37.7% (CI 95%: 35.5; 39.8%) had a restless leg syndrome. When comparing cities, significant differences in the overall frequency of subjects requiring care were found between Santa Marta (higher frequency) and the other two cities. Differences in sleep problem frequency (Pittsburgh) were observed between Bogota (higher frequency) and Bucaramanga and also between Santa Marta (higher frequency) and the other two cities. The high risk of OSA (STOP-Bang) was different between Bogota (higher frequency) and Bucaramanga and also between Santa Marta (high frequency) and Bucaramanga.ConclusionsWe observed a high prevalence of sleep complaints with significant differences among the cities, indicating a need to pay a greater attention to these problems