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Open reading frame (ORF) 50 protein is capable of activating the entire lytic cycle of Kaposi's sarcomaassociated herpesvirus (KSHV), but its mechanism of action is not well characterized. Here we demonstrate that ORF 50 protein activates two KSHV lytic cycle genes, PAN (polyadenylated nuclear RNA) and K12, by binding to closely related response elements located approximately 60 to 100 nucleotides (

The authors suggested acceptance criteria for rural dispersion models' performance measures in this journal in 2004. The current paper suggests modified values of acceptance criteria for urban applications and tests them with tracer data from four urban field experiments. For the arc-maximum concentrations, the fractional bias should have a magnitude\0.67 (i.e., the relative mean bias is less than a factor of 2); the normalized mean-square error should be \6 (i.e., the random scatter is less than about 2.4 times the mean); and the fraction of predictions that are within a factor of two of the observations (FAC2) should be [0.3. For all data paired in space, for which a threshold concentration must always be defined, the normalized absolute difference should be \0.50, when the threshold is three times the instrument's limit of quantification (LOQ). An overall criterion is then applied that the total set of acceptance criteria should be satisfied in at least half of the field experiments. These acceptance criteria are applied to evaluations of the US Department of Defense's Joint Effects Model (JEM) with tracer data from US urban field experiments in Salt Lake City (U2000), Oklahoma City (JU2003), and Manhattan (MSG05 and MID05). JEM includes the SCIPUFF dispersion model with the urban canopy option and the urban dispersion model (UDM) option. In each set of evaluations, three or four likely options are tested for meteorological inputs (e.g., a local building top wind speed, the closest National Weather Service airport observations, or outputs from numerical weather prediction models). It is found that, due to large natural variability in the urban data, there is not a large difference between the performance measures for the two model options and the three or four meteorological input options. The more detailed UDM and the state-of-the-art numerical weather models do provide a slight improvement over the other options. The proposed urban dispersion model acceptance criteria are satisfied at over half of the field experiments.

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Results of evaluations of transport and dispersion models with field data are summarized. The California Puff (CALPUFF), Hazard Prediction and Assessment Capability (HPAC), and Chemical/Biological Agent Vapor, Liquid, and Solid Tracking (VLSTRACK) models were compared using two recent mesoscale field datasetsthe Dipole Pride 26 (DP26) and the Overland Along-wind Dispersion (OLAD). Both field experiments involved instantaneous releases of sulfur hexafluoride tracer gas in a mesoscale region with desert basins and mountains. DP26 involved point sources, and OLAD involved line sources. Networks of surface wind observations and special radiosonde and pilot balloon soundings were available, and tracer concentrations were observed along lines of whole-air samplers and some fast-response instruments at distances up to 20 km. The models were evaluated using the maximum 3-h dosage (concentration integrated over time) along a sampling line. It was found that the solutions were highly dependent upon the diagnostic wind field model used to interpolate the spatially variable observed wind fields. At the DP26 site, CALPUFF and HPAC had better performance than VLSTRACK. Overall, the three models had mean biases within 35% and random scatters of about a factor of 3-4. About 50%-60% of CALPUFF and HPAC predictions and about 40% of VLSTRACK predictions were within a factor of 2 of observations. At the OLAD site, all three models underpredicted by a factor of 2-3, on average, with random scatters of a factor of 3-7. About 50% of HPAC predictions and only 25%-30% of CALPUFF and VLSTRACK predictions were within a factor of 2 of observations.