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The Diffuse X‐ray emission from the Local Galaxy (DXL) sounding rocket is a NASA approved mission with a scheduled first launch in December 2012. Its goal is to identify and separate the X‐ray emission of the solar wind charge exchange (SWCX) from that of the local hot bubble (LHB) to improve our understanding of both. To separate the SWCX contribution from the LHB, DXL will use the SWCX signature due to the helium focusing cone at l = 185°, b = –18°. DXL uses large area proportional counters, with an area of 1000 cm2 and grasp of about 10 cm2 sr both in the 1/4 and 3/4 keV bands. Thanks to the large grasp, DXL will achieve in a 5‐minute flight what cannot be achieved by current and future X‐ray satellites (© 2012 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)  相似文献   
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On 2001 March 31 a coronal mass ejection pushed the subsolar magnetopause to the vicinity of geosynchronous orbit at 6.6 RE. The NASA/GSFC Community Coordinated Modeling Center (CCMC) employed a global magnetohydrodynamic (MHD) model to simulate the solar wind‐magnetosphere interaction during the peak of this geomagnetic storm. Robertson et al. then modeled the expected soft X‐ray emission due to solar wind charge exchange with geocoronal neutrals in the dayside cusp and magnetosheath. The locations of the bow shock, magnetopause and cusps were clearly evident in their simulations. Another geomagnetic storm took place on 2000 July 14 (Bastille Day). We again modeled X‐ray emission due to solar wind charge exchange, but this time as observed from a moving spacecraft. This paper discusses the impact of spacecraft location on observed X‐ray emission and the degree to which the locations of the bow shock and magnetopause can be detected in images (© 2012 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)  相似文献   
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In a continuing effort to develop inexpensive source tracking methods to detect human fecal contamination in environmental waters, targeted sampling was combined with fluorometry. Targeted sampling works by identifying hot spots of fecal contamination through multiple samplings over ever-decreasing distances. Fluorometry identifies human fecal contamination by detecting optical brighteners, primarily from laundry detergents. Because organic matter fluoresces and interferes with fluorometry, two locations were chosen for sampling: waters relatively low in organic matter at Mayagüez Bay, Puerto Rico, and waters relatively high in organic matter at St. Simons Island, Georgia. In Puerto Rico, targeted sampling and fluorometry quickly and easily identified two hot spots of human fecal contamination in the Yagüez River, which flows through the city of Mayagüez. Another source tracking method, detection of theesp gene, confirmed their human origin. On St. Simous Island, targeted sampling and fiuorometry identified two hot spots of potential human fecal contamination. Detection of theesp gene confirmed the human origin of one site but not the other, most likely because background organic matter fluorescence interfered with fhiorometry. A separate experiment showed that adding a 436-um emission filter to the fluorometer reduced this background fluorescence by > 50%. With the 436-nm Filter in place, another sampling was conducted on St. Simons Island, and the second hot spot was identified as fecal contamination from birds. As long as the fluorometer was equipped with a 436-nm filter and organic matter concentrations were considered, targeted sampling combined with fluorometry was a relatively inexpensive method for identifying human fecal contamination in water.  相似文献   
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We describe current progress in the development of a prototype wide field‐of‐view soft X‐ray imager that employs Lobster‐eye optics and targets heliophysics, planetary, and astrophysics science. The prototype will provide proof‐of‐concept for a future flight instrument capable of imaging the entire dayside magnetosheath from outside the magnetosphere. Such an instrument was proposed for the ESA AXIOM mission (© 2012 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)  相似文献   
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Small-sized housing samples and price predictions at nonobserved locations require geostatistical approaches, particularly the kriging estimator. Nevertheless, geostatistics has thus far received little attention in real estate economics. The article’s objective is to empirically compare the prediction accuracy of univariate kriging variants, namely detrended kriging (DK) and universal kriging (UK), and multivariate extensions, including detrended cokriging (DCK) and universal cokriging (UCK). Both latter methods consider structural and neighborhood characteristics as auxiliary variables. While the price surfaces of DK and UK show nearly identical cross-validated accuracies, the cross-validation-based prediction accuracy of DCK and UCK differ in favor of the latter. If real estate agencies are faced with a univariate sample of property prices, either DK or UK can be used, while in the multivariate case, UCK is recommended, although numerically more complex.  相似文献   
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