Fluid flow in simulated rigid network and adapted network for network with 5 endothelial cells.

<p>In adapted network, some segments eliminated because their diameter is small and they pass very low flow. In both cases, when a segment’s flow rate is less than 0.01 of the maximum flow rate in the network, this segment is pruned.</p

Interstitial pressure distribution in the same tumor ().

<p>Interstitial pressure distribution in the same tumor ().</p

Cross sectional schematic of a solid tumor that shows the three different regions of a solid tumor, IFP distribution, drug concentration and filtration distribution from blood vessels.

<p>Cross sectional schematic of a solid tumor that shows the three different regions of a solid tumor, IFP distribution, drug concentration and filtration distribution from blood vessels.</p

Effect of Temperature on the Surface Tension of 1-Hexanol Aqueous Solutions

This paper describes the effect of temperature on the surface tension and adsorption kinetics of 1-hexanol aqueous solutions. The experiments were performed in a closed chamber where both liquid and vapor phases coexisted, and the surface tension was influenced by a combination of liquid and vapor phase adsorption. The surface tension of 1-hexanol aqueous solutions at steady-state was found to decrease upon an increase in temperature, and a linear relationship was observed between them. The modified Langmuir equation of state and the modified kinetic transfer equation were used to model the experimental data of the steady-state and dynamic (time-dependent) surface tension, respectively. The equilibrium constants and adsorption rate constants were evaluated through nonlinear regression for temperatures ranging from 10 to 35 °C. From the steady-state modeling, the equilibrium constants for adsorption from vapor phase and liquid phase were found to increase with temperature. From the dynamic modeling, the adsorption rate constants for adsorption from vapor phase and liquid phase were found to increase with temperature too. Small deviations from the experimental data have been observed in the dynamic modeling. These deviations may be due to the experimental errors or more likely the limitations of the model used

Algorithm for calculating interstitial pressure in tissue without considering capillary network.

<p>Algorithm for calculating interstitial pressure in tissue without considering capillary network.</p

Fluid flow in simulated rigid network and adapted network for network with 10 endothelial cells.

<p>In adapted network, some segments eliminated because their diameter is small and they pass very low flow. In both cases, when a segment’s flow rate is less than 0.01 of the maximum flow rate in the network, this segment is pruned.</p

Material properties used in numerical simulations, as taken from [13].

<p>Material properties used in numerical simulations, as taken from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0020344#pone.0020344-Jain7" target="_blank">[13]</a>.</p

Three dimensional plot of Fig. 6, dimensionless interstitial pressure distribution, in the same tumor ().

<p>Three dimensional plot of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0020344#pone-0020344-g006" target="_blank">Fig. 6</a>, dimensionless interstitial pressure distribution, in the same tumor ().</p

Schematic of different patterns of blood flow in networks a) Blood flow from one (two) node(s) into one (two) node(s).

<p>b) Blood flow from three nodes into one node. c) Blood flow from one node into three nodes.</p

Interstitial velocity distribution in a 1 cm radius tumor, different values of , Eq. (16).

<p>Interstitial velocity distribution in a 1 cm radius tumor, different values of , Eq. (16).</p