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The Varre-Sai meteorite fell along the border of the states of Espirito Santo and Rio de Janeiro, Brazil; on 19 June 2010 at 5:40 pm. Petrography and X-ray powder diffraction (XRD) indicate that the rock is an L5 S4 chondrite, with blastoporphyritic texture that has not been previously described. Geochemical data based on major and rare-earth elements (REEs) show that Varre-Sai is highly similar to the other L chondrites. In Harker diagrams, Varre-Sai, L, and LL chondrites form a single group, suggesting no significant chemical differences between them and contributing to the long-standing debate of whether LL chondrites form a distinct group or whether they are a subset of the L group. Harker diagrams also define a trend from E to H and L/LL chondrites, similar to the cosmochemical trends suggested by other authors. The behaviour of Fe2O3t and NiO indicates a relationship with Fe-Ni alloys, and their trend in the diagram suggests some chemical differentiation in the ordinary chondrite parental bodies. The REE content in Varre-Sai, normalized to C chondrites, falls in the field of L chondrites and others, but with slight REE enrichment. The chemical differences in chondrites, mainly in REEs, Fe2O3t and NiO could be alternatively interpreted as variations in the inherited agglutinated materials as chondrules, Ca–Al-rich inclusions and Fe–Ni nodules.  相似文献   
956.
Iranian strong motion records as well as detailed conditions of their instrument sites and the characteristics of their causative seismic sources are compiled and processed. The dataset consists of 2286 three-component records from 461 Iranian earthquakes with at least two high-quality records having moment magnitude from 3.9 to 7.3. These records are about 20% of the Iranian database and are suitable for seismic hazard analysis and engineering applications. Perhaps for the first time in the literature, the distance to the surface projection of the fault is reported for a great number of records corresponding to earthquakes with M > 6.0. The raw accelerations are processed using the wavelet de-noising method. Having corrected and filtered these raw data, the pseudospectral accelerations are calculated for each of the three components of time series, separately. In addition to the ground motion parameters, a large and comprehensive list of metadata characterizing the recording conditions of each record is also developed. Moreover, careful revision of the characteristics of the earthquakes such as location, magnitude, style of faulting and fault rupture plane geometry, if available, is carried out using the best available information in a scientifically sound manner. Finally, we also focus on special ground motion records including records with peak ground acceleration (PGA) >300 cm/s2 and distances less than 30 km. These are “exceptional” records in the Iranian dataset and include less than 2% of the selected dataset.  相似文献   
957.
Natural Hazards - In November 2015, China government announced that the national carbon emissions trading market is expected to start in 2017. Carbon emission trading system is a raising concern...  相似文献   
958.
Mineralogy and Petrology - Borate minerals of the ludwigite group (LGM) and szaibélyite in association with hydroxylclinohumite, clinochlore, a serpentine mineral, magnesian magnetite, spinel,...  相似文献   
959.
Mineralogy and Petrology - The platiniferous gold–palladium belt of Minas Gerais, Brazil, forms an approximately 240-km-long, roughly north–south-trending domain that includes numerous...  相似文献   
960.
This study demonstrated the usefulness of very long-range terrestrial laser scanning (TLS) for analysis of the spatial distribution of a snowpack, to distances up to 3000 m, one of the longest measurement range reported to date. Snow depth data were collected using a terrestrial laser scanner during 11 periods of snow accumulation and melting, over three snow seasons on a Pyrenean hillslope characterized by a large elevational gradient, steep slopes, and avalanche occurrence. The maximum and mean absolute snow depth error found was 0.5-0.6 and 0.2-0.3 m respectively, which may result problematic for areas with a shallow snowpack, but it is sufficiently accurate to determine snow distribution patterns in areas characterized by a thick snowpack. The results indicated that in most cases there was temporal consistency in the spatial distribution of the snowpack, even in different years. The spatial patterns were particularly similar amongst the surveys conducted during the period dominated by snow accumulation (generally until end of April), or amongst those conducted during the period dominated by melting processes (generally after mid of April or early May). Simple linear correlation analyses for the 11 survey dates, and the application of Random Forests analysis to two days representative of snow accumulation and melting periods indicated the importance of topography to the snow distribution. The results also highlight that elevation and the Topographic Position index (TPI) were the main variables explaining the snow distribution, especially during periods dominated by melting. The intra- and inter-annual spatial consistency of the snowpack distribution suggests that the geomorphological processes linked to presence/absence of snow cover act in a similar way in the long term, and that these spatial patterns can be easily identified through several years of adequate monitoring.  相似文献   
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