Micro-crystalline inclusions analysis by PIXE and RBS

A characteristic feature of the nuclear microprobe using a 3 MeV proton beam is the long range of particles (around 70 \mu m in light matrices). The PIXE method, with EDS analysis and using the multilayer approach for treating the X-ray spectrum allows the chemistry of an intra-crystalline inclusion to be measured, provided the inclusion roof and thickness at the impact point of the beam (Z and e, respectively) are known (the depth of the inclusion floor is Z + e). The parameter Z of an inclusion in a mineral can be measured with a precision of around 1 \mu m using a motorized microscope. However, this value may significantly depart from Z if the analyzed inclusion has a complex shape. The parameter e can hardly be measured optically. By using combined RBS and PIXE measurements, it is possible to obtain the geometrical information needed for quantitative elemental analysis. This paper will present measurements on synthetic samples to investigate the advantages of the technique, and also on natural solid and fluid inclusions in quartz. The influence of the geometrical parameters will be discussed with regard to the concentration determination by PIXE. In particular, accuracy of monazite micro-inclusion dating by coupled PIXE-RBS will be presented

Characterization of Three Carbon- and Nitrogen-Rich Particles from Comet 81P/WILD

Comets may sample the early solar system s complement of volatile-forming elements - including C and N - more fully and reliably than do the terrestrial planets or asteroids. Until recently, all elemental analyses of unambiguously cometary material were carried out remotely. The return of the Stardust mission makes it possible to analyze documented material from P81/Wild 2 in the laboratory Wild 2 particles fragmented when they stopped in the aerogel collectors. We have studied three fragments thought to be rich in C and N by using several techniques: FTIR to characterize organic matter; synchrotron-induced x-ray fluorescence (SXRF) to determine Fe and certain element/Fe ratios; SEM to image sample morphology and to detect semiquantitatively Mg, Al, Si, Ca, and Fe; and nuclear reaction analysis (NRA) to measure C, N, O, and Si

Evaluación del riesgo de inundación a múltiples componentes en la costa del Maresme

The coast is one of the areas most affected by natural hazards, with floods being the most frequent and significant of these in terms of their induced impacts, so any management scheme requires their evaluation. In coastal areas, flooding is a hazard associated with different processes acting at different scales: coastal storms, flash floods and sea level rise (SLR). To address the problem as a whole, this study presents a methodology to undertake a preliminary integrated risk assessment of the magnitude of each flood component, taking into account their scope (extension of the affected area) and their temporal scale. The risk is quantified using specific indicators to assess the hazard magnitude (for each component) and the consequences. This allows for a robust comparison of the spatial risk distribution along the coast in order to identify both the most at-risk areas and the most influential risk components. This methodology is applied to a stretch of coastline (Maresme, Catalonia) representative of the Spanish Mediterranean coast. The results obtained characterise this coastline as an area with a relatively low overall risk, although some hotspots are identified as having high-risk values. Resumen: La costa es una de las zonas más sometidas a riesgos naturales, siendo la inundación uno de los más frecuentes e importantes en términos de daños inducidos, por lo que cualquier esquema de gestión requiere evaluación. La inundación en zonas costeras es una amenaza natural asociada a diferentes procesos que actúan a distintas escalas: tormentas costeras, riadas y subida del nivel del mar (SNM). Para abarcar la totalidad del problema, este trabajo propone una metodología para la evaluación preliminar del riesgo integrado de inundación costera a una escala regional que permite evaluar la magnitud de cada componente teniendo en cuenta su alcance (extensión de la zona afectada) y su escala temporal. El riesgo se cuantifica en función de unos indicadores específicos que valoran la magnitud de la amenaza para cada componente y las consecuencias. Esto permite comparar robustamente la distribución espacial del riesgo a lo largo de la costa, para identificar tanto zonas de mayor riesgo como las componentes que más contribuyen al mismo. Aplicamos esta metodología a un tramo de costa característica del Mediterráneo español (Maresme, Cataluña). Los resultados permiten caracterizar esta costa como un área con un riesgo global relativamente bajo, pero algunos puntos singulares con riesgo alto

Building ProteomeTools based on a complete synthetic human proteome.

We describe ProteomeTools, a project building molecular and digital tools from the human proteome to facilitate biomedical research. Here we report the generation and multimodal liquid chromatography-tandem mass spectrometry analysis of \u3e330,000 synthetic tryptic peptides representing essentially all canonical human gene products, and we exemplify the utility of these data in several applications. The resource (available at http://www.proteometools.org) will be extended to \u3e1 million peptides, and all data will be shared with the community via ProteomicsDB and ProteomeXchange

Efficacy of a nucleoside-sparing regimen of darunavir/ritonavir plus raltegravir in treatment-naive HIV-1-infected patients (ACTG A5262)

To explore darunavir/ritonavir (DRV/r) plus raltegravir (RAL) combination therapy in antiretroviral-naive patients

Climatic predictors of species distributions neglect biophysiologically meaningful variables

This is the final version. Available on open access from Wiley via the DOI in this record.Aim: Species distribution models (SDMs) have played a pivotal role in predicting how species might respond to climate change. To generate reliable and realistic predictions from these models requires the use of climate variables that adequately capture physiological responses of species to climate and therefore provide a proximal link between climate and their distributions. Here, we examine whether the climate variables used in plant SDMs are different from those known to influence directly plant physiology. Location: Global. Methods: We carry out an extensive, systematic review of the climate variables used to model the distributions of plant species and provide comparison to the climate variables identified as important in the plant physiology literature. We calculate the top ten SDM and physiology variables at 2.5 degree spatial resolution for the globe and use principal component analyses and multiple regression to assess similarity between the climatic variation described by both variable sets. Results: We find that the most commonly used SDM variables do not reflect the most important physiological variables and differ in two main ways: (i) SDM variables rely on seasonal or annual rainfall as simple proxies of water available to plants and neglect more direct measures such as soil water content; and (ii) SDM variables are typically averaged across seasons or years and overlook the importance of climatic events within the critical growth period of plants. We identify notable differences in their spatial gradients globally and show where distal variables may be less reliable proxies for the variables to which species are known to respond. Main conclusions: There is a growing need for the development of accessible, fine-resolution global climate surfaces of physiological variables. This would provide a means to improve the reliability of future range predictions from SDMs and support efforts to conserve biodiversity in a changing climate