The following inequality is from Vapnik Statistical learning theory p.128 which I have no idea how to solve the following set of inequalities. In the context, $R(\alpha), R_{emp}(\alpha)$ are random variables, so the following inequalities are considered pointwisely.
Given \begin{align*} \epsilon = \sqrt{2\frac{\ln(N)-\ln\eta}{l}}, \qquad \frac{R(\alpha)-R_{emp}(\alpha)}{\sqrt{R(\alpha})}\leq \epsilon \end{align*}
It concludes
\begin{align} R(\alpha) < R_{emp}(\alpha)+\frac{\ln N-\ln\eta}{l}\left(1+ \sqrt{1 + 2\frac{R_{emp}(\alpha)l}{\ln N-\ln\eta}}\right) \end{align}
If written in $\epsilon$, it is of the form \begin{align} R(\alpha)<R_{emp}(\alpha)+ \frac{\epsilon^2}{2}\left(1+ \sqrt{1 + \frac{4 R_{emp}(\alpha)}{\epsilon^2}}\right) \end{align}
My attempt is like \begin{align} \frac{R(\alpha)-R_{emp}(\alpha)}{\sqrt{R(\alpha})}\leq \epsilon \quad &\Longleftrightarrow \quad R(\alpha)-R_{emp}(\alpha)\leq \epsilon \sqrt{R(\alpha})\\ &\Longleftrightarrow \quad R(\alpha)\leq R_{emp}(\alpha)+ \epsilon \sqrt{R(\alpha})\\ &\Longrightarrow \quad R(\alpha)\leq R_{emp}(\alpha)+ \epsilon \sqrt{\epsilon \sqrt{R(\alpha)}+R_{emp}(\alpha)}\\ &\Longrightarrow \quad R(\alpha)\leq R_{emp}(\alpha)+ \frac{\epsilon^2}{2}\sqrt{\frac{4\sqrt{R(\alpha)}}{\epsilon}+\frac{4R_{emp}(\alpha)}{\epsilon^2}} \end{align}
Somehow this is pretty closed to the target inequality. However, I just have no idea how to complete the last step. Also, in the context it is known \begin{align} 0\leq R(\alpha), R_{emp}(\alpha)\leq 1 \end{align} Does anyone have any idea?
Thanks in advance!