Our objective was to evaluate the function of treahlose and erythritol in reducing ROS concentrations, which is associated with a general improvement in the quality of frozen-thawing miniature pig sperm. Semen was mixed in modified Modena B extender, added to cooling media and freezing media, followed by the supplement of 100 mM trehalose and/or 100 mM erythritol with spermatozoa (1000x 109cells/straw). The trehalose plus erythritol (TE) added group had less intracellular H2O2 than did control and trehalose (36.6±1.6 vs. 49.0±5.8 and 48.8±7.9; P<0.05). The percentage of viable acrosome-intact sperm (FITC-PNA-/PI-) was higher in erythritol and TE than controls (57.0±5.5% and 62.5±4.3% vs. 45.4±5.4%; P<0.05 and P<0.001). The percentage of sperm with high fragmented DNA was observed in control group when compared with erythritol and TE also trehalose (65.5±1.3% vs 59.3±0.7% and 59.0±0.3% vs 62.2± 0.8%; P<0.001). The percentage of sperm LPO was higher in control and trehalose than erythritol (4.4±0.5% and 5.0±0.5% vs. 3.5±0.2; P<0.01 and P<0.001), and was lowest in the TE (control and trehalose vs. TE: P<0.001, erythritol vs. TE: P<0.05). Also, we performed that surgical insemination based on above data to evaluate the function of new cryoprotectant such as trehalose plus erythritol in vivo. Finally, 1 pregnant gilt showed natural estrus was allowed to go to term and 8 live piglets were born. In conclusion, miniature pig sperm was successfully cryopreserved with trehalose plus erythritol provided the increasing the sperm quality and reducing the ROS.

The relationship between debris flow and topographical factors is essential for the reliable estimation of soil loss. The objective of this paper is to estimate stability index and soil loss for assessing landsliding risk caused by debris flow. SIMAP and RUSLE are used to estimate stability index and soil loss, respectively. The landsliding risk area estimated by using SIMAP is found to be different from the large land area estimated by RUSLE. It is found that the spatial distribution of soil cover significantly influences landsliding risk area. Results also indicate that stability index and soil loss, estimated by soil cover factor, improve the assessment of landsliding risk.

This study applied the Bayesian method for the quantification of the parameter uncertainty of spatial linear mixed model in the estimation of the spatial distribution of probability rainfall. In the application of Bayesian method, the prior sensitivity analysis was implemented by using the priors normally selected in the existing studies which applied the Bayesian method for the puppose of assessing the influence which the selection of the priors of model parameters had on posteriors. As a result, the posteriors of parameters were differently estimated which priors were selected, and then in the case of the prior combination, F-S-E, the sizes of uncertainty intervals were minimum and the modes, means and medians of the posteriors were similar to the estimates using the existing classical methods. From the comparitive analysis between Bayesian and plug-in spatial predictions, we could find that the uncertainty of plug-in prediction could be slightly underestimated than that of Bayesian prediction.