Expression analysis of four Pinus radiata male cone promoters in the heterologous host Arabidopsis

Four male cone-specific promoters were isolated from the genome of Pinus radiata D. Don, fused to the beta-glucuronidase (GUS) reporter gene and analysed in the heterologous host Arabidopsis thaliana (L.) Heynh. The temporal and spatial activities of the promoters PrCHS1, PrLTP2, PrMC2 and PrMALE1 during seven anther developmental stages are described in detail. The two promoters PrMC2 and PrMALE1 confer an identical GUS expression pattern on Arabidopsis anthers. DNA sequence analysis of the PrMC2 and PrMALE1 promoters revealed an 88% sequence identity over 276 bp and divergence further upstream (

Adsorption of supercritical fluids in non-porous and porous carbons: analysis of adsorbed phase volume and density

In this paper, we revisit the surface mass excess in adsorption studies and investigate the role of the volume of the adsorbed phase and its density in the analysis of supercritical gas adsorption in non-porous as well as microporous solids. For many supercritical fluids tested (krypton, argon, nitrogen, methane) on many different carbonaceous solids, it is found that the volume of the adsorbed phase is confined mostly to a geometrical volume having a thickness of up to a few molecular diameters. At high pressure the adsorbed phase density is also found to be very close to but never equal or greater than the liquid phase density. (C) 2003 Elsevier Science Ltd. All rights reserved.

Methodologies for calibration and predictive analysis of a watershed model

The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.