Search results for "g(1)"
showing 10 items of 717 documents
"Figure 11" of "Cold-nuclear-matter effcts on heavy-quark production in d+Au collisions at sqrt(s_NN)=200 GeV"
2023
Heavy flavor electron $R_{dA}$ 60-88% $d$+Au collisions. The nuclear modification factor, $R_{dA}$, for electrons from open heavy flavor decays, for the (a) most central and (b) most peripheral centrality bins.
"Figure 8" of "Cold-nuclear-matter effcts on heavy-quark production in d+Au collisions at sqrt(s_NN)=200 GeV"
2023
Heavy flavor electron RdA 0-20% $d$+Au collisions. The nuclear modification factor, $R_{dA}$, for electrons from open heavy flavor decays, for the (a) most central and (b) most peripheral centrality bins.
"Figure 9" of "Cold-nuclear-matter effcts on heavy-quark production in d+Au collisions at sqrt(s_NN)=200 GeV"
2023
Heavy flavor electron $R_{dA}$ 20-40% $d$+Au collisions. The nuclear modification factor, $R_{dA}$, for electrons from open heavy flavor decays, for the (a) most central and (b) most peripheral centrality bins.
"Figure 7" of "Cold-nuclear-matter effcts on heavy-quark production in d+Au collisions at sqrt(s_NN)=200 GeV"
2023
Heavy flavor electron $R_{dA}$ 0-100% d+Au collisions. The nuclear modification factors $R_{dA}$ and $R_{AA}$ for minimum bias $d$+Au and Au+Au collisions, for the $\pi^{0}$ and $e^{\pm}_{HF}$. The two boxes on the right side of the plot represent the global uncertainties in the $d$+Au (left) and Au+Au (right) values of $N_{coll}$ . An additional common global scaling uncertainty of 9.7% on $R_{dA}$ and $R_{AA}$ from the $p+p$ reference data is omitted for clarity.
"Figures 3-6" of "Cold-nuclear-matter effcts on heavy-quark production in d+Au collisions at sqrt(s_NN)=200 GeV"
2023
Heavy flavor electron yield, $d$+Au $\implies$ CHARGED X. Electrons from heavy flavor decays, separated by centrality. The lines represent a fit to the previous $p+p$ result [23], scaled by $N_{coll}$. The inset shows the ratio of photonic background electrons determined by the converter and cocktail methods for Minimum Bias $d$+Au collisions, with error bars (boxes) that represent the statistical uncertainty on the converter data (systematic uncertainty on the photonic-electron cocktail).
"Figure 10" of "Cold-nuclear-matter effcts on heavy-quark production in d+Au collisions at sqrt(s_NN)=200 GeV"
2023
Heavy flavor electron $R_{dA}$ 40-60% $d$+Au collisions. The nuclear modification factor, $R_{dA}$, for electrons from open heavy flavor decays, for the (a) most central and (b) most peripheral centrality bins.
"Figures 1-2" of "Cold-nuclear-matter effcts on heavy-quark production in d+Au collisions at sqrt(s_NN)=200 GeV"
2023
Heavy flavor electron yield, Run-8 $p$ + $p$, $d$+Au collisions. Electrons from heavy flavor decays, separated by centrality. The lines represent a fit to the previous $p+p$ result [23], scaled by $N_{coll}$. The inset shows the ratio of photonic background electrons determined by the converter and cocktail methods for Minimum Bias $d$+Au collisions, with error bars (boxes) that represent the statistical uncertainty on the converter data (systematic uncertainty on the photonic-electron cocktail).
LAI, FAPAR and FCOVER ground-truth map creation from FASat-C satellite imagery and in-situ measurements in Chimbarongo, Chile, for satellite products…
2016
[EN] In remote sensing, validation exercises are essential to ensure the quality of the products originated from satellite Earth observations. To assess the measurement uncertainty derived from satellite products, several ground field data from different ecosystems must be available for use. In the same order of importance, it is necessary to define data sampling and up-scaling methodologies to allow a suitable comparison between the ground data and the pixel size of the product. This paper shows the applied methodology used in the FP7 ImagineS project (Implementing Multi-scale Agricultural Indicators Exploiting Sentinels) to validate 10-days global LAI, FAPAR and vegetation cover products …
Vegetation vulnerability to drought in Spain
2014
[EN] Frequency of climatic extremes like long duration droughts has increased in Spain over the last century.The use of remote sensing observations for monitoring and detecting drought is justified on the basis that vegetation vigor is closely related to moisture condition. We derive satellite estimates of bio-physical variables such as fractional vegetation cover (FVC) from MODIS/EOS and SEVIRI/MSG time series. The study evaluates the strength of temporal relationships between precipitation and vegetation condition at time-lag and cumulative rainfall intervals. From this analysis, it was observed that the climatic disturbances affected both the growing season and the total amount of vegeta…
Analysing the effect of land use and vegetation cover on soil infiltration in three contrasting environments in northeast Spain
2017
Este estudio presenta el análisis conjunto de la información obtenida a partir de 195 ensayos de infiltración en el campo, que fueron realizados mediante dispositivos de doble anillo. Los experimentos se realizaron en 20 situaciones contrastadas de usos del suelo, los cuales se encuentran distribuidos en tres contextos geográficos (costa NE de Cataluña, monte bajo del sector central del valle del Ebro y montaña media de la vertiente Sur del Pirineo central). El objetivo de esta investigación es determinar los factores más importantes que explican la variabilidad de la infiltración: uso del suelo, tipo de cubierta vegetal, características del suelo y del substrato rocoso, humedad del suelo y…