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In this study, a machine learning method, i.e. genetic programming (GP), is employed to obtain a simplified statistical model to describe the variation of soil suction in drying cycles using five selected influential parameters. The data used for model development was recorded by an in-situ experiment. The image processing technology is used to quantify several tree canopy parameters. Based on four accuracy metrics, i.e. root mean square error (RMSE), mean absolute percentage error (MAPE), coefficient of determination (R2), and relative error, the performance of the proposed GP model was evaluated. The results indicate that the model can give a reasonable estimation for the spatiotemporal variations of soil suction around a tree with acceptable errors. Global sensitivity analysis for the statistical model obtained using limited data of a specific region demonstrates the drying time as the most influential variable and the initial soil suction as the second most influential variable for the soil suction variations. A case study was conducted using a set of assumed input variable values and validated that the simplified GP model can be used to estimate and predict the spatiotemporal variations of soil suction in rooted soil at a certain range.

To prepare lidocaine nanoemulsion and investigate its transdermal delivery ability in vitro.The optimal Km (surfactant/cosurfactant) value and the component proportion were determined by pseudoternary phase diagrams combined with Origin software analysis. The diameter and distribution range were detected by Zeta particle size analysis instrument, and the morphology of the nanoemulsion was observed by electron microscope. The permeation flux of lidocaine was determined in vitro using the modified Franz diffusion cell combined with HPLC, and the cumulative transdermal absorption amount and the apparent skin transdermal velocity were compared among nanoemulsion, gel and tincture containing 5% lidocaine. The permeation mode of lidocaine nanoemulsion was analyzed.The average drop size of lidocaine nanoemulsion was 29.8-/+14.4 nm, and 98% of the drop sizes ranged from 15.1 to 45.5 nm and 2% from 77.9 to 261.3 nm. The nanoemulsion drop showed a spherical morphology in a polydisperse system. The Kp value of the nanoemulsion (3.07-/+0.74 cm/h) was significantly higher than that of gel (1.27-/+0.35 cm/h) and tincture (0.97-/+0.18 cm/h), and the permeation rate of the nanoemulsion was 69.82-/+7.48 microg x cm(-2) x h(-1), which fitted the the Zero-order release dynamic procedure.The component proportion of lidocaine nanoemulsion can be conveniently obtained through pseudoternary phase diagrams and Origin software analysis, and the drop size, distribution, morphology and system type can be determined by Malvern Zetasizer combined with electron microscopy. The results also indicate that the nanoemulsion system with high permeation rate may provide a new promising means for local anesthesia.