(003-008)** New Features** (04/02/16/JPR): The Conversion Types within the Utilities | Solid | Convert | **Solid -> Grid** and **Solid -> Zones** programs have been significantly enhanced:

- (003) The conversion types have been moved from the tree-style menu into a new dialog box in order to incorporated explanatory text and four new conversions.

- (004) A new
**Median**conversion has been added. Select this option to compute the median node G value in each vertical column of the solid model, and store that G value in the corresponding grid node. The statistical median is the number separating the higher half of the sampling from the lower half. It is often a better representation of the “average” (versus the mean) when a distribution is skewed by outliers.

- (005) A new
**Most Frequently Occurring G-Value**conversion has been added. Select this option to compute the most frequently occurring node G value (the mode) in each vertical column of the solid model, and store that G value in the corresponding grid node. Note: This doesn’t work well for multimodal populations (i.e. vertical columns where there are “ties” for the most frequently occuring G values). In these cases, the program will arbritarily choose the first candidate. Also note that selecting this option will require significantly more time for performing the solid-to-grid conversion.

- (006) A new
**Number of Non-Null Voxels**conversion has been added. Select this option to count the number of non-null (>-1.0e26) G values in each vertical column of the solid model, and store that count in the corresponding grid node.

- (007) A new
**Number of Null Voxels**conversion has been added. Select this option to count the number of null (=-1.0e27) G values in each vertical column of the solid model, and store that count in the corresponding grid node.

- (008) A new
**Standard Deviation**conversion has been added. Select this option to compute the Standard Deviation of all the non-null nodes within each version column of the solid model, and store that count in the corresponding grid node. With some data sets, this number is an approximation of the vertical anisotropy (i.e. square root of variance).

The example below shows how these new conversions apply to an interpolated block model of Lead concentrations: