FORECASTING GYPSY MOTH DEFOLIATION WITH A GEOGRAPHICAL INFORMATION SYSTEM
In this study, we developed a series of logistic regression models for forecasting gypsy moth de-foliation. The models were parameterized by using data collected over a small scaled l00m×100m grid-area; the independent variables included egg mass density, male moth trap, previous year defoliation, and distance to the nearest cell which was defoliated in the previous year. We simulated the decision-making by using these models; this method essentially simulated the application of current gypsy moth management decision-making. The results indicated that these models can be more reliably applied to actual manage-ment decision.
Objective: Search for the right de-foaming methods for bio-artificial liver system. Material and methods: Choose harmless material to animal's cell and physical de-foaming methods. Results and Conclusion: We have found out the effective and feasible methods through comparing some methods' results. This methods' merit is that it don't change the ingredient and physical condition of the medium.