New empirical model to evaluate groundwater flow into circular tunnel using multiple regression analysis

There are various analytical, empirical and numerical methods to calculate groundwater inflow into tun- nels excavated in rocky media. Analytical methods have been widely applied in prediction of groundwa- ter inflow to tunnels due to their simplicity and practical base theory. Investigations show that the real amount of water infiltrating into jointed tunnels is much less than calculated amount using analytical methods and obtained results are very dependent on tunnel＇s geometry and environmental situations. In this study, using multiple regression analysis, a new empirical model for estimation of groundwater seepage into circular tunnels was introduced. Our data was acquired from field surveys and laboratory analysis of core samples. New regression variables were defined after perusing single and two variables relationship between groundwater seepage and other variables. Finally, an appropriate model for estima- tion of leakage was obtained using the stepwise algorithm. Statistics like R, R2, R2e and the histogram of residual values in the model represent a good reputation and fitness for this model to estimate the groundwater seepage into tunnels. The new experimental model was used for the test data and results were satisfactory. Therefore, multiple regression analysis is an effective and efficient way to estimate the groundwater seeoage into tunnels.

The analysis of tax policy based on Kim Gordon model

Economic decide taxes and taxes have an adverse effect on the economy. To achieve a sustained development of economy, we must require the taxes which are closely related to economy meet the requirements of its own development. That is tax receipts raised by government meeting functional needs as much as possible, while reducing the facts that will damage the future needs and development of economy. Therefore, we need to analyze various factors that affect revenue. If we make a very good understanding on how structure impacting on tax revenues, that will help us to use policy tools tax making impacts on revenue and optimize the structure of the tax. For this theme, many domestic scholars have done correlation research, and their research paper provides a good reference, but we believe their research can be further refined. Through theoretical analysis, we can select appropriate indicators letting tax revenue to be explained variable. Each possible influencing factor of tax revenues establish measurement model for explaining variable using stepwise regression models, and make a rigorous statistical test on the model. On the base of fully proving the effectiveness of the model, we can make relevant economic analysis.

A Rhodamine-Based Sensor for Chromogenic Detection of Cu^(2+) and Fluorescent Detection of Fe^(3+)

A rhodamine-benzimidazole conjugate （RB） as a probe was investigated. UV-Vis analysis showed that a strong absorption band at 552 nm was formed with the addition of Cu^2＋, while other transition metal ions induced a little more absorption. The absorption value of RB solution at 552 nm has a linear correlation with Cu^2＋ concentration between 35-70 μmol/L; the detection limit reached 6.82x 10-2 gmol/L, which is lower than the settled limitation for copper in the drinking water （-30 μmol/L） standardized by World Health Organization （WHO）. Moreover, FL analysis showed that only Fe^3＋ could induce large fluorescence intensity enhance- ment at 582 nm; other common metal ions including Cu^2＋ cannot induce the enhancement. There was a good linear correlation be Fe^3＋ tween relatwe fluorescence ntenslty and Fe concentration ranging from 2 μmol/L to 20 μmol/L, and the detection limit reached 1.70×10^-2 μmol/L. The results showed that RB could detect Cu^2＋ and Fe^3＋ simultaneously, with the UV-Vis and fluorescence spectroscopy, respectively.