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Describing convective nonwetting phase flow in unsaturated porous media requires knowledge of the nonwetting phase relative permeability. This study was conducted to formulate and derive a generalized expression for the nonwetting phase relative permeability via combining with the Kosugi water retention function. This generalized formulation is then used to flexibly investigate the Burdine, Mualem, and Alexander and Skaggs models' prediction accuracy for relative nonwetting phase permeability. The model and data comparison results show that these three permeability models, if used in their original form, but applied to the nonwetting phase, could not predict the experimental data well. The optimum pore tortuosity and connectivity value is thus obtained for the improved prediction of relative nonwetting phase permeability. As a result, the effective parameterization of (a; b; g) parameters in the modified Burdine, modified Mualem, and modified Alexander and Skaggs permeability models were found to be (2.5, 2, 1), (2, 1, 2), and (2.5, 1, 1), respectively. These three suggested models display the highest accuracy among the nine relative permeability models investigated in this study. However, the corresponding discontinuous nonwetting phase and the liquid film flow should be accounted for in future for the improved prediction of nonwetting phase relative permeability at very high and very low water saturation range, respectively.

The temporal dynamics of vegetation biomass are of key importance for evaluating the sustainability of arid and semiarid ecosystems. In these ecosystems, biomass and soil moisture are coupled stochastic variables externally driven, mainly, by the rainfall dynamics. Based on long-term field observations in northwestern (NW) China, we test a recently developed analytical scheme for the description of the leaf biomass dynamics undergoing seasonal cycles with different rainfall characteristics. The probabilistic characterization of such dynamics agrees remarkably well with the field measurements, providing a tool to forecast the changes to be expected in biomass for arid and semiarid ecosystems under climate change conditions. These changes will depend-for each season-on the forecasted rate of rainy days, mean depth of rain in a rainy day, and duration of the season. For the site in NW China, the current scenario of an increase of 10% in rate of rainy days, 10% in mean rain depth in a rainy day, and no change in the season duration leads to forecasted increases in mean leaf biomass near 25% in both seasons.ecohydrology | stochastic dynamics | vegetation modeling | climate change impacts | soil moisture I n arid and semiarid ecosystems, successful use of limited water resources is of central importance in determining the evolutionary trends of vegetation. Soil moisture there is the principal limiting factor for vegetation restoration and plays a key role in controlling the spatiotemporal patterns of vegetation regulating the complex dynamics of the climate-soil-vegetation system (1, 2).Characterizing the vegetation in water-limited ecosystems, with regard to quantity, species composition, and stability, is a long-standing problem in restoration ecology (3). Field surveys and different types of measurements have been taken for decades (4), but they have mostly yielded only descriptive results [e.g., links between soil moisture and accompanying biomass (5)].Schaffer et al. (3) recently developed an analytical description of the transient joint behavior of plant biomass and soil moisture induced by stochastic rainfall dynamics. These analytical results allow for predictions of ecosystem behavior under changing climate conditions and also illuminate the sensitivities of the dynamics to plant physiology, as well as to climate and soil characteristics that govern the system. The objective of this study is first to test the accuracy of the analytical model under current conditions by comparing its predicted distribution for the biomass density in both the wet and dry seasons with the statistics observed in a long-term field experiment in northwestern (NW) China. Subsequently, using the climate change forecast of the field site, predictions will be made for the seasonal mean biomass and its variability in the future.Ecosystem Characteristics: Climate, Soil, and Vegetation Long-term detailed measurements of vegetation dynamics were carried out at the plant level in four plots located at the Shapotou Desert Research and Experi...

First, the SA-TDZA-Lips were prepared by reverse-phase evaporation method. Then, the drug release behaviour was evaluated by dynamic membrane dialysis in vitro and the preliminary safety was evaluated by haemolysis method. Finally, with tedizolid phosphate injection (TDZA-Inj) and tedizolid phosphate loaded liposomes (TDZA-Lips) as the control groups, the pharmacokinetic characteristic and tissues distribution of SA-TDZA-Lips were evaluated after intravenous injection. As a result, the stearylamine modified tedizolid phosphate liposomal delivery system was constructed successfully and the particle size was 194.9 ± 2.93 nm. The encapsulation efficiency (EE) was 53.52 ± 2.18%. The in vitro release of SA-TDZA-Lips was in accordance with Weibull equation. And there was no haemolysis happened, which indicated good preliminary safety for injection. The results of pharmacokinetics showed that the t1/2β increased by 0.74 times and 0.51 times higher than that of TDZA-Inj group and TDZA-Lips group, respectively. The MRT of SA-TDZA-Lips was 1.30 and 1.09 times higher than that of TDZA-Inj group and TDZA-Lips group, respectively. The AUC was 2.40 times and 0.23 times higher than that of TDZA-Inj group and TDZA-Lips group, respectively. The tissue distribution results showed that the relative uptake rate (Re) of TDZA in the lung was 1.527, which indicated the targeting. In conclusion, the SA-TDZA-Lips prepared in this study had several advantages like positive charge, strong cell affinity, prolonged circulation time in vivo, sustained release effect, and increased drug concentration in lungs. All advantages above provided significant clinical value of application for the treatment of bacterial pneumonia with tedizolid phosphate.

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Biodegradable particles are extremely useful in the development of novel drug delivery systems. Recent studies have suggested that morphology can influence the mechanisms of drug delivery in many ways. In the present study, biodegradable microparticles with different morphologies were prepared from poly(L‑lactide) (PLA) using the electrospraying technique. The microparticles were then systematically examined by scanning using an electron microscope. The results revealed that the preparation of drug-loaded microspheres through electrospraying is a simple and efficient method, and the processing parameters, such as polymer molecular weight, concentration, surfactant and solvent play an important role in obtaining high quality microcarriers. The association between microcarrier morphology and the processing parameters used was also investigated. Rifampin-loaded PLA microspheres were also prepared according to the above-mentioned model. Our data demonstrate that the drug release from PLA microspheres can be sustained in vitro for over 60 h. Our study focused on obtaining electrosprayed medicated microparticles from complex polyester particles. Further studies are required to explore the potential commercial use of these microparticles.

Modeling convective air movement in unsaturated porous media requires appropriate characterization of the relative air permeability (RAP). Adopting Assouline et al. (1998, https://doi.org/10.1029/97WR03039) water retention function that is based on the Weibull pore size distribution, this study was conducted to derive seven new predictive RAP models. These 7 new models, together with another 3 models developed by Assouline et al. (2016, https://doi.org/10.1002/2015WR018286), were then compared with data from 30 disturbed soil samples to investigate their predictive RAP performances. The model and data comparison results showed that the modified Burdine, modified Mualem, and modified Alexander and Skaggs relative permeability models proposed by Yang and Mohanty (2015, https://doi.org/10.1002/2014WR016190) had the highest accuracy for the RAP prediction among the 10 investigated models, which indicated that the tortuosity and connectivity exponent of water phase should be smaller than that of air phase for the disturbed soil samples. The modified Burdine, modified Mualem, and modified Alexander and Skaggs models were then the suggested RAP parameterizations for the subsurface multiphase flow numerical simulation.

Abstract:The present investigation deals with the study of