Step 1: Understanding pH.
The pH scale is logarithmic and measures the concentration of hydrogen ions \([H^+]\). The formula for pH is: \[ {pH} = -\log[H^+] \] Thus, a solution with pH 7 has a hydrogen ion concentration of \([H^+] = 10^{-7}\) mol/L, and a solution with pH 6 has \([H^+] = 10^{-6}\) mol/L.
Step 2: Mixing the two solutions.
When two solutions are mixed, the resulting concentration of \([H^+]\) is the average of the two concentrations, as the volumes are equal. The combined concentration of hydrogen ions is: \[ [H^+]_{{mix}} = \frac{(10^{-7} + 10^{-6})}{2} = \frac{1.1 \times 10^{-6}}{2} = 5.5 \times 10^{-7} \] Step 3: Calculating the resulting pH.
Now, we calculate the pH of the resulting solution: \[ {pH}_{{mix}} = -\log(5.5 \times 10^{-7}) = 6.26 \] Therefore, the resulting pH of the mixture is approximately \(6.26\).
While doing Bayesian inference, consider estimating the posterior distribution of the model parameter (m), given data (d). Assume that Prior and Likelihood are proportional to Gaussian functions given by \[ {Prior} \propto \exp(-0.5(m - 1)^2) \] \[ {Likelihood} \propto \exp(-0.5(m - 3)^2) \] 
The mean of the posterior distribution is (Answer in integer)
Consider a medium of uniform resistivity with a pair of source and sink electrodes separated by a distance \( L \), as shown in the figure. The fraction of the input current \( (I) \) that flows horizontally \( (I_x) \) across the median plane between depths \( z_1 = \frac{L}{2} \) and \( z_2 = \frac{L\sqrt{3}}{2} \), is given by \( \frac{I_x}{I} = \frac{L}{\pi} \int_{z_1}^{z_2} \frac{dz}{(L^2/4 + z^2)} \). The value of \( \frac{I_x}{I} \) is equal to 
Suppose a mountain at location A is in isostatic equilibrium with a column at location B, which is at sea-level, as shown in the figure. The height of the mountain is 4 km and the thickness of the crust at B is 1 km. Given that the densities of crust and mantle are 2700 kg/m\(^3\) and 3300 kg/m\(^3\), respectively, the thickness of the mountain root (r1) is km. (Answer in integer)