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Institution

University of Maryland, Baltimore County

EducationBaltimore, Maryland, United States
About: University of Maryland, Baltimore County is a education organization based out in Baltimore, Maryland, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 8749 authors who have published 20843 publications receiving 795706 citations. The organization is also known as: UMBC.


Papers
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Journal ArticleDOI
TL;DR: In this article, a two-stage statistical model driven by gap-filled AOD, meteorology and land use information was then fitted to estimate daily ground PM 2.5 concentrations in 2013 and 2014 at 1-km resolution with complete coverage in space and time.

236 citations

Journal ArticleDOI
TL;DR: Efforts to identify the molecular determinants and mechanism of human immunodeficiency virus type 1 genome packaging are reviewed.

236 citations

Journal ArticleDOI
TL;DR: Modification of DNA bases in mammalian chromatin upon treatment with hydrogen peroxide in the presence of ferric and cupric ions was studied, indicating a possible site-specific formation of hydroxyl radical when metal ions are bound to chromatin.

236 citations

Journal ArticleDOI
TL;DR: It is suggested that this remarkable ability of circularly polarized light mediates sexual signaling and mate choice, although other potential functions of circular polarization vision, such as enhanced contrast in turbid environments, are also possible.

235 citations

Journal ArticleDOI
TL;DR: In this article, five Microtops II sun photometers were studied in detail at the NASA Goddard Space Flight Center (GSFC) to determine their performance in measuring aerosol optical thickness (AOT or Tau(sub alphalambda) and precipitable column water vapor (W).
Abstract: Five Microtops II sun photometers were studied in detail at the NASA Goddard Space Flight Center (GSFC) to determine their performance in measuring aerosol optical thickness (AOT or Tau(sub alphalambda) and precipitable column water vapor (W). Each derives Tau(sub alphalambda) from measured signals at four wavelengths lambda (340, 440, 675, and 870 nm), and W from the 936 nm signal measurements. Accuracy of Tau(sub alphalambda) and W determination depends on the reliability of the relevant channel calibration coefficient (V(sub 0)). Relative calibration by transfer of parameters from a more accurate sun photometer (such as the Mauna-Loa-calibrated AERONET master sun photometer at GSFC) is more reliable than Langley calibration performed at GSFC. It was found that the factory-determined value of the instrument constant for the 936 nm filter (k= 0.7847) used in the Microtops' internal algorithm is unrealistic, causing large errors in V(sub 0(936)), Tau(sub alpha936), and W. Thus, when applied for transfer calibration at GSFC, whereas the random variation of V(aub 0) at 340 to 870 nm is quite small, with coefficients of variation (CV) in the range of 0 to 2.4%, at 936 nm the CV goes up to 19%. Also, the systematic temporal variation of V(sub 0) at 340 to 870 nm is very slow, while at 936 nm it is large and exhibits a very high dependence on W. The algorithm also computes Tau(sub alpha936) as 0.91Tau(sub alpha870), which is highly simplistic. Therefore, it is recommended to determine Tau(sub alpha936) by logarithmic extrapolation from Tau(sub alpha675) and Tau(sub alpha 870. From the operational standpoint of the Microtops, apart from errors that may result from unperceived cloud contamination, the main sources of error include inaccurate pointing to the Sun, neglecting to clean the front quartz window, and neglecting to calibrate correctly. If these three issues are adequately taken care of, the Microtops can be quite accurate and stable, with root mean square (rms) differences between corresponding retrievals from clean calibrated Microtops and the AERONET sun photometer being about +/-0.02 at 340 nm, decreasing down to about +/-0.01 at 870 nm.

235 citations


Authors

Showing all 8862 results

NameH-indexPapersCitations
Robert C. Gallo14582568212
Paul T. Costa13340688454
Igor V. Moskalenko13254258182
James Chiang12930860268
Alex K.-Y. Jen12892161811
Alan R. Shuldiner12055771737
Richard N. Zare120120167880
Vince D. Calhoun117123462205
Rita R. Colwell11578155229
Kendall N. Houk11299754877
Elliot K. Fishman112133549298
Yoram J. Kaufman11126359238
Paulo Artaxo10745444346
Braxton D. Mitchell10255849599
Sushil Jajodia10166435556
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202371
2022165
20211,065
20201,091
2019989
2018929