University of Maryland, Baltimore County

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.

Analysis of Multiple Precipitation Products and Preliminary Assessment of Their Impact on Global Land Data Assimilation System Land Surface States

Abstract: Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. NASA's Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type). Precipitation is arguably the most important input to LSMs. Many precipitation datasets have been produced using satellite and rain gauge observations and weather forecast models. In this study, seven different global precipitation datasets were evaluated over the United States, where dense rain gauge networks contribute to reliable precipitation maps. We then used the seven datasets as inputs to GLDAS simulations, so that we could diagnose their impacts on output stocks and fluxes of water. In terms of totals, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) had the closest agreement with the US rain gauge dataset for all seasons except winter. The CMAP precipitation was also the most closely correlated in time with the rain gauge data during spring, fall, and winter, while the satellitebased estimates performed best in summer. The GLDAS simulations revealed that modeled soil moisture is highly sensitive to precipitation, with differences in spring and summer as large as 45% depending on the choice of precipitation input.

High-resolution X-ray spectroscopy and modeling of the absorbing and emitting outflow in NGC 3783

Abstract: The high-resolution X-ray spectrum of NGC 3783 shows several dozen absorption lines and a few emission lines from the H-like and He-like ions of O, Ne, Mg, Si, and S, as well as from Fe XVII-Fe XXIII L-shell transitions. We have reanalyzed the Chandra HETGS spectrum using better flux and wavelength calibrations, along with more robust methods. Combining several lines from each element, we clearly demonstrate the existence of the absorption lines and determine that they are blueshifted relative to the systemic velocity by -610 ? 130 km s-1. We find the Ne absorption lines in the High-Energy Grating spectrum to be resolved with FWHM = 840 km s-1; no other lines are resolved. The emission lines are consistent with being at the systemic velocity. We have used regions in the spectrum where no lines are expected to determine the X-ray continuum, and we model the absorption and emission lines using photoionized-plasma calculations. The model consists of two absorption components, with different covering factors, which have an order-of-magnitude difference in their ionization parameters. The two components are spherically outflowing from the active galactic nucleus, and thus contribute to both the absorption and the emission via P Cygni profiles. The model also clearly requires O VII and O VIII absorption edges. The low-ionization component of our model can plausibly produce UV absorption lines with equivalent widths consistent with those observed from NGC 3783. However, we note that this result is highly sensitive to the unobservable UV to X-ray continuum, and the available UV and X-ray observations cannot firmly establish the relationship between the UV and X-ray absorbers. We find good agreement between the Chandra spectrum and simultaneous ASCA and RXTE observations. The 1 keV deficit previously found when modeling ASCA data probably arises from iron L-shell absorption lines not included in previous models. We also set an upper limit on the FWHM of the narrow Fe K? emission line of 3250 km s-1. This is consistent with this line originating outside the broad-line region, possibly from a torus.

Diurnal variability of aerosol optical depth observed at AERONET (Aerosol Robotic Network) sites

Abstract: [1] Diurnal variability of aerosol optical depth is important for various applications, including satellite aerosol data validation, radiative forcing computations, studies of aerosol interaction with humidity and clouds, and also public health. Aerosol optical depth measurements acquired through the ground-based Aerosol Robotic Network are analyzed. Analysis of the diurnal cycle over major urban/industrial areas within the network showed a prevailing pattern of the optical depth increase by 10–40% during the day at most sites. Diurnal variability range is <10% over various sites where dust aerosol is a major contributor to optical depth. Sites in southern Africa influenced by distant sources of biomass burning aerosol show no diurnal cycle, while the presence of local sources causes a diurnal trend with a maximum aerosol loading observed in the afternoon hours. Over oceans, because of the very low optical depth, even 20% departure from the daily average is practically within the measurement uncertainty.

Coping with Node Misbehaviors in Ad Hoc Networks: A Multi-dimensional Trust Management Approach

Abstract: Nodes in Mobile Ad hoc Networks (MANETs) are required to relay data packets to enable communication between other nodes that are not in radio range with each other. However, whether for selfish or malicious reasons, a node may fail to cooperate during the network operations or even attempt to disturb them, both of which have been recognized as misbehaviors. Various trust management schemes have been studied to assess the behaviors of nodes so as to detect and mitigate node misbehaviors inMANETs. Most of existing schemes model a node's trustworthiness along a single dimension, combining all of the available evidence to calculate a single, scalar trust metric. A single measure, however, may not be expressive enough to adequately describe a node's trustworthiness in many scenarios. In this paper, we describe a multi-dimensional framework to evaluate the trustworthiness of MANET node from multiple perspectives. Our scheme evaluates trustworthiness from three perspectives: collaboration trust, behavioral trust, and reference trust. Different types of observations are used to independently derive values for these three trust dimensions. We present simulation results that illustrate the effectiveness of the proposed scheme in several scenarios.

Immunohistochemical differentiation of high-grade prostate carcinoma from urothelial carcinoma.

Abstract: The histologic distinction between high-grade prostate cancer and infiltrating high-grade urothelial cancer may be difficult, and has significant implications because each disease may be treated very differently (ie, hormone therapy for prostate cancer and chemotherapy for urothelial cancer). Immuno