Index: src/sas/perspectives/fitting/media/fitting.rst
===================================================================
--- src/sas/perspectives/fitting/media/fitting.rst	(revision cfc591725433447b38e307a0ce2e3b7a53288db2)
+++ src/sas/perspectives/fitting/media/fitting.rst	(revision f256d9bcf2609af134abad50102230b4af3acd45)
@@ -5,9 +5,9 @@
    :maxdepth: 1
 
-   Fitting Perspective <fitting_help>
+   Fitting Data <fitting_help>
 
    Polydispersity Distributions <pd_help>
 
-   Smearing Computation <sm_help>
+   Smearing Functions <sm_help>
 
    Polarisation/Magnetic Scattering <mag_help>
Index: src/sas/perspectives/fitting/media/pd_help.rst
===================================================================
--- src/sas/perspectives/fitting/media/pd_help.rst	(revision 892a2cc1d960c97bc94500f5915d62c8bac0c979)
+++ src/sas/perspectives/fitting/media/pd_help.rst	(revision f256d9bcf2609af134abad50102230b4af3acd45)
@@ -11,4 +11,5 @@
 .. |theta| unicode:: U+03B8
 .. |chi| unicode:: U+03C7
+.. |Ang| unicode:: U+212B
 
 .. |inlineimage004| image:: sm_image004.gif
@@ -28,28 +29,29 @@
 ----------------------------
 
-Calculates the form factor for a polydisperse and/or angular population of 
-particles with uniform scattering length density. The resultant form factor 
-is normalized by the average particle volume such that 
-
-P(q) = scale*\<F*F\>/Vol + bkg
-
-where F is the scattering amplitude and the\<\>denote an average over the size 
-distribution.  Users should use PD (polydispersity: this definition is 
-different from the typical definition in polymer science) for a size 
-distribution and Sigma for an angular distribution (see below).
-
-Note that this computation is very time intensive thus applying polydispersion/
-angular distribution for more than one parameters or increasing Npts values
-might need extensive patience to complete the computation. Also note that 
-even though it is time consuming, it is safer to have larger values of Npts 
-and Nsigmas.
-
-The following five distribution functions are provided
+With some models SasView can calculate the average form factor for a population
+of particles that exhibit size and/or orientational polydispersity. The resultant
+form factor is normalized by the average particle volume such that
+
+*P(q) = scale* * \ <F*\F> / *V + bkg*
+
+where F is the scattering amplitude and the \<\> denote an average over the size
+distribution.
+
+Users should note that this computation is very intensive. Applying polydispersion
+to multiple parameters at the same time, or increasing the number of *Npts* values
+in the fit, will require patience! However, the calculations are generally more
+robust with more data points or more angles.
+
+SasView uses the term *PD* for a size distribution (and not to be confused with a
+molecular weight distributions in polymer science) and the term *Sigma* for an
+angular distribution.
+
+The following five distribution functions are provided:
 
 *  *Rectangular Distribution*
-*  *Array Distribution*
 *  *Gaussian Distribution*
 *  *Lognormal Distribution*
 *  *Schulz Distribution*
+*  *Array Distribution*
 
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
@@ -58,9 +60,12 @@
 ^^^^^^^^^^^^^^^^^^^^^^^^
 
+The Rectangular Distribution is defined as
+
 .. image:: pd_image001.png
 
-The xmean is the mean of the distribution, w is the half-width, and Norm is a 
-normalization factor which is determined during the numerical calculation. 
-Note that the Sigma and the half width *w*  are different.
+where *xmean* is the mean of the distribution, *w* is the half-width, and *Norm* is a
+normalization factor which is determined during the numerical calculation.
+
+Note that the standard deviation and the half width *w* are different!
 
 The standard deviation is
@@ -68,9 +73,87 @@
 .. image:: pd_image002.png
 
-The PD (polydispersity) is
+whilst the polydispersity is
 
 .. image:: pd_image003.png
 
 .. image:: pd_image004.jpg
+
+.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
+
+Gaussian Distribution
+^^^^^^^^^^^^^^^^^^^^^
+
+The Gaussian Distribution is defined as
+
+.. image:: pd_image005.png
+
+where *xmean* is the mean of the distribution and *Norm* is a normalization factor
+which is determined during the numerical calculation.
+
+The polydispersity is
+
+.. image:: pd_image003.png
+
+
+.. image:: pd_image006.jpg
+
+.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
+
+Lognormal Distribution
+^^^^^^^^^^^^^^^^^^^^^^
+
+The Lognormal Distribution is defined as
+
+.. image:: pd_image007.png
+
+where |mu|\ =ln(*xmed*), *xmed* is the median value of the distribution, and
+*Norm* is a normalization factor which will be determined during the numerical
+calculation.
+
+The median value for the distribution will be the value given for the respective
+size parameter in the *Fitting Perspective*, for example, radius = 60.
+
+The polydispersity is given by |sigma|
+
+.. image:: pd_image008.png
+
+For the angular distribution
+
+.. image:: pd_image009.png
+
+The mean value is given by *xmean*\ =exp(|mu|\ +p\ :sup:`2`\ /2). The peak value
+is given by *xpeak*\ =exp(|mu|-p\ :sup:`2`\ ).
+
+.. image:: pd_image010.jpg
+
+This distribution function spreads more, and the peak shifts to the left, as *p*
+increases, requiring higher values of Nsigmas and Npts.
+
+.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
+
+Schulz Distribution
+^^^^^^^^^^^^^^^^^^^
+
+The Schulz distribution is defined as
+
+.. image:: pd_image011.png
+
+where *xmean* is the mean of the distribution and *Norm* is a normalization factor
+which is determined during the numerical calculation, and *z* is a measure of the
+width of the distribution such that
+
+z = (1-p\ :sup:`2`\ ) / p\ :sup:`2`
+
+The polydispersity is
+
+.. image:: pd_image012.png
+
+Note that larger values of PD might need larger values of Npts and Nsigmas.
+For example, at PD=0.7 and radius=60 |Ang|, Npts>=160 and Nsigmas>=15 at least.
+
+.. image:: pd_image013.jpg
+
+For further information on the Schulz distribution see:
+M Kotlarchyk & S-H Chen, *J Chem Phys*, (1983), 79, 2461.
 
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
@@ -79,86 +162,40 @@
 ^^^^^^^^^^^^^^^^^^
 
-This distribution is to be given by users as a txt file where the array 
-should be defined by two columns in the order of x and f(x) values. The f(x) 
+This user-definable distribution should be given as as a simple ASCII text file
+where the array is defined by two columns of numbers: *x* and *f(x)*. The *f(x)*
 will be normalized by SasView during the computation.
 
-Example of an array in the file
-
-30        0.1
-32        0.3
-35        0.4
-36        0.5
-37        0.6
-39        0.7
-41        0.9
-
-We use only these array values in the computation, therefore the mean value 
-given in the control panel, for example Ã¢â¬Ëradius = 60Ã¢â¬â¢, will be ignored.
-
-.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
-
-Gaussian Distribution
-^^^^^^^^^^^^^^^^^^^^^
-
-.. image:: pd_image005.png
-
-The xmean is the mean of the distribution and Norm is a normalization factor 
-which is determined during the numerical calculation.
-
-The PD (polydispersity) is
-
-.. image:: pd_image003.png
-
-.. image:: pd_image006.jpg
-
-.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
-
-Lognormal Distribution
-^^^^^^^^^^^^^^^^^^^^^^
-
-.. image:: pd_image007.png
-
-The /mu/=ln(xmed), xmed is the median value of the distribution, and Norm is a 
-normalization factor which will be determined during the numerical calculation. 
-The median value is the value given in the size parameter in the control panel, 
-for example, Ã¢â¬Åradius = 60Ã¢â¬ï¿œ.
-
-The PD (polydispersity) is given by /sigma/
-
-.. image:: pd_image008.png
-
-For the angular distribution
-
-.. image:: pd_image009.png
-
-The mean value is given by xmean=exp(/mu/+p2/2). The peak value is given by 
-xpeak=exp(/mu/-p2).
-
-.. image:: pd_image010.jpg
-
-This distribution function spreads more and the peak shifts to the left as the 
-p increases, requiring higher values of Nsigmas and Npts.
-
-.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
-
-Schulz Distribution
-^^^^^^^^^^^^^^^^^^^
-
-.. image:: pd_image011.png
-
-The xmean is the mean of the distribution and Norm is a normalization factor
-which is determined during the numerical calculation.
-
-The z = 1/p2Ã¢â¬â 1.
-
-The PD (polydispersity) is
-
-.. image:: pd_image012.png
-
-Note that the higher PD (polydispersity) might need higher values of Npts and 
-Nsigmas. For example, at PD = 0.7 and radisus = 60 A, Npts >= 160, and 
-Nsigmas >= 15 at least.
-
-.. image:: pd_image013.jpg
-
-.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
+Example of what an array distribution file should look like:
+
+====  =====
+ 30    0.1
+ 32    0.3
+ 35    0.4
+ 36    0.5
+ 37    0.6
+ 39    0.7
+ 41    0.9
+====  =====
+
+SasView only uses these array values during the computation, therefore any mean
+value of the parameter represented by *x* present in the *Fitting Perspective*
+will be ignored.
+
+.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
+
+Note about DLS polydispersity
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Many commercial Dynamic Light Scattering (DLS) instruments produce a size
+polydispersity parameter, sometimes even given the symbol *p*! This parameter is
+defined as the relative standard deviation coefficient of variation of the size
+distribution and is NOT the same as the polydispersity parameters in the Lognormal
+and Schulz distributions above (though they all related) except when the DLS
+polydispersity parameter is <0.13.
+
+For more information see:
+S King, C Washington & R Heenan, *Phys Chem Chem Phys*, (2005), 7, 143
+
+.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
+
+.. note::  This help document was last changed by Steve King, 01May2015
Index: src/sas/perspectives/fitting/media/sm_help.rst
===================================================================
--- src/sas/perspectives/fitting/media/sm_help.rst	(revision cfc591725433447b38e307a0ce2e3b7a53288db2)
+++ src/sas/perspectives/fitting/media/sm_help.rst	(revision f256d9bcf2609af134abad50102230b4af3acd45)
@@ -11,4 +11,5 @@
 .. |theta| unicode:: U+03B8
 .. |chi| unicode:: U+03C7
+.. |bigdelta| unicode:: U+0394
 
 .. |inlineimage004| image:: sm_image004.gif
@@ -25,8 +26,14 @@
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
 
-Smearing Computation
---------------------
-
-The following three smearing algorithms are provided
+Smearing Functions
+==================
+
+Sometimes it will be necessary to correct reduced experimental data for the
+physical effects of the instrumental geometry in use. This process is called
+*desmearing*. However, calculated/simulated data - which by definition will be
+perfect/exact - can be *smeared* to make it more representative of what might
+actually be measured experimentally.
+
+SasView provides the following three smearing algorithms:
 
 *  *Slit Smearing*
@@ -37,24 +44,27 @@
 
 Slit Smearing
-^^^^^^^^^^^^^
-
-The sit smeared scattering intensity for SAS is defined by
+-------------
+
+**This type of smearing is normally only encountered with data from X-ray Kratky**
+**cameras or X-ray/neutron Bonse-Hart USAXS/USANS instruments.**
+
+The slit-smeared scattering intensity is defined by
 
 .. image:: sm_image002.gif
 
-where Norm =
+where *Norm* is given by
 
 .. image:: sm_image003.gif
 
-Equation 1
+**[Equation 1]**
 
 The functions |inlineimage004| and |inlineimage005|
 refer to the slit width weighting function and the slit height weighting 
-determined at the q point, respectively. Here, we assumes that the weighting 
-function is described by a rectangular function, i.e.,
+determined at the given *q* point, respectively. It is assumed that the weighting
+function is described by a rectangular function, such that
 
 .. image:: sm_image006.gif
 
-Equation 2
+**[Equation 2]**
 
 and
@@ -62,123 +72,128 @@
 .. image:: sm_image007.gif
 
-Equation 3
-
-so that |inlineimage008| |inlineimage009| for |inlineimage010| and u.
-
-The |inlineimage011| and |inlineimage012| stand for
-the slit height (FWHM/2) and the slit width (FWHM/2) in the q space. Now the 
-integral of Equation 1 is simplified to
+**[Equation 3]**
+
+so that |inlineimage008| |inlineimage009| for |inlineimage010| and *u*\ .
+
+Here |inlineimage011| and |inlineimage012| stand for
+the slit height (FWHM/2) and the slit width (FWHM/2) in *q* space.
+
+This simplifies the integral in Equation 1 to
 
 .. image:: sm_image013.gif
 
-Equation 4
-
-Numerical Implementation of Equation 4: Case 1
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-For |inlineimage012| = 0 and |inlineimage011| = constant.
+**[Equation 4]**
+
+which may be solved numerically, depending on the nature of |inlineimage011| and |inlineimage012| .
+
+Solution 1
+^^^^^^^^^^
+
+**For** |inlineimage012| **= 0 and** |inlineimage011| **= constant.**
 
 .. image:: sm_image016.gif
 
-For discrete q values, at the q values from the data points and at the q 
-values extended up to qN= qi + |inlineimage011| the smeared 
-intensity can be calculated approximately
+For discrete *q* values, at the *q* values of the data points and at the *q*
+values extended up to *q*\ :sub:`N`\ = *q*\ :sub:`i` + |inlineimage011| the smeared
+intensity can be approximately calculated as
 
 .. image:: sm_image017.gif
 
-Equation 5
-
-|inlineimage018| = 0 for *Is* in *j* < *i* or *j* > N-1*.
-
-Numerical Implementation of Equation 4: Case 2
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-For |inlineimage012| = constant and |inlineimage011| = 0.
-
-Similarly to Case 1, we get
-
-|inlineimage019| for qp= qi- |inlineimage012| and qN= qi+ |inlineimage012|. |inlineimage018| = 0
-for *Is* in *j* < *p* or *j* > *N-1*.
-
-Numerical Implementation of Equation 4: Case 3
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-For |inlineimage011| = constant and 
-|inlineimage011| = constant.
-
-In this case, the best way is to perform the integration, Equation 1, 
-numerically for both slit height and width. However, the numerical integration 
-is not correct enough unless given a large number of iteration, say at least 
-10000 by 10000 for each element of the matrix, W, which will take minutes and 
-minutes to finish the calculation for a set of typical SAS data. An 
-alternative way which is correct for slit width << slit hight, is used in 
-SasView. This method is a mixed method that combines method 1 with the 
-numerical integration for the slit width.
+**[Equation 5]**
+
+where |inlineimage018| = 0 for *I*\ :sub:`s` when *j* < *i* or *j* > *N-1*.
+
+Solution 2
+^^^^^^^^^^
+
+**For** |inlineimage012| **= constant and** |inlineimage011| **= 0.**
+
+Similar to Case 1
+
+|inlineimage019| for *q*\ :sub:`p` = *q*\ :sub:`i` - |inlineimage012| and *q*\ :sub:`N` = *q*\ :sub:`i` + |inlineimage012|
+
+**[Equation 6]**
+
+where |inlineimage018| = 0 for *I*\ :sub:`s` when *j* < *p* or *j* > *N-1*.
+
+Solution 3
+^^^^^^^^^^
+
+**For** |inlineimage011| **= constant and** |inlineimage011| **= constant.**
+
+In this case, the best way is to perform the integration of Equation 1
+numerically for both slit height and slit width. However, the numerical
+integration is imperfect unless a large number of iterations, say, at
+least 10000 by 10000 for each element of the matrix *W*, is performed.
+This is usually too slow for routine use.
+
+An alternative approach is used in SasView which assumes
+slit width << slit height. This method combines Solution 1 with the
+numerical integration for the slit width. Then
 
 .. image:: sm_image020.gif
 
-Equation 7
-
-for qp= qi- |inlineimage012| and
-qN= qi+ |inlineimage012|. |inlineimage018| = 0 for
-*Is* in *j* < *p* or *j* > *N-1*.
+**[Equation 7]**
+
+for *q*\ :sub:`p` = *q*\ :sub:`i` - |inlineimage012| and *q*\ :sub:`N` = *q*\ :sub:`i` + |inlineimage012|
+
+where |inlineimage018| = 0 for *I*\ :sub:`s` when *j* < *p* or *j* > *N-1*.
 
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
 
 Pinhole Smearing
-^^^^^^^^^^^^^^^^
-
-The pinhole smearing computation is done similar to the case above except 
-that the weight function used is the Gaussian function, so that the Equation 6 
-for this case becomes
+----------------
+
+**This is the type of smearing normally encountered with data from synchrotron**
+**SAXS cameras and SANS instruments.**
+
+The pinhole smearing computation is performed in a similar fashion to the slit-
+smeared case above except that the weight function used is a Gaussian. Thus
+Equation 6 becomes
 
 .. image:: sm_image021.gif
 
-Equation 8
-
-For all the cases above, the weighting matrix *W* is calculated when the 
-smearing is called at the first time, and it includes the ~ 60 q values 
-(finely binned evenly) below (\>0) and above the q range of data in order 
-to cover all data points of the smearing computation for a given model and 
-for a given slit size. The *Norm*  factor is found numerically with the 
-weighting matrix, and considered on *Is* computation.
+**[Equation 8]**
 
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
 
 2D Smearing
-^^^^^^^^^^^
-
-The 2D smearing computation is done similar to the 1D pinhole smearing above 
-except that the weight function used was the 2D elliptical Gaussian function
+-----------
+
+The 2D smearing computation is performed in a similar fashion to the 1D pinhole
+smearing above except that the weight function used is a 2D elliptical Gaussian.
+Thus
 
 .. image:: sm_image022.gif
 
-Equation 9
-
-In Equation 9, x0 = qcos/theta/ and y0 = qsin/theta/, and the primed axes 
-are in the coordinate rotated by an angle /theta/ around the z-axis (below) 
-so that xÃ¢â¬â¢0= x0cos/theta/+y0sin/theta/ and yÃ¢â¬â¢0= -x0sin/theta/+y0cos/theta/.
-
-Note that the rotation angle is zero for x-y symmetric elliptical Gaussian 
-distribution. The A is a normalization factor.
+**[Equation 9]**
+
+In Equation 9, *x*\ :sub:`0` = *q* cos(|theta|), *y*\ :sub:`0` = *q* sin(|theta|), and
+the primed axes, are all in the coordinate rotated by an angle |theta| about
+the z-axis (see the figure below) so that *x'*\ :sub:`0` = *x*\ :sub:`0` cos(|theta|) +
+*y*\ :sub:`0` sin(|theta|) and *y'*\ :sub:`0` = -*x*\ :sub:`0` sin(|theta|) +
+*y*\ :sub:`0` cos(|theta|). Note that the rotation angle is zero for a x-y symmetric
+elliptical Gaussian distribution. The *A* is a normalization factor.
 
 .. image:: sm_image023.gif
 
-Now we consider a numerical integration where each bins in /theta/ and R are 
-*evenly* (this is to simplify the equation below) distributed by /delta//theta/ 
-and /delta/R, respectively, and it is assumed that I(xÃ¢â¬â¢, yÃ¢â¬â¢) is constant 
-within the bins which in turn becomes
+Now we consider a numerical integration where each of the bins in |theta| and *R* are
+*evenly* (this is to simplify the equation below) distributed by |bigdelta|\ |theta|
+and |bigdelta|\ R, respectively, and it is further assumed that *I(x',y')* is constant
+within the bins. Then
 
 .. image:: sm_image024.gif
 
-Equation 10
-
-Since we have found the weighting factor on each bin points, it is convenient 
-to transform xÃ¢â¬â¢-yÃ¢â¬â¢ back to x-y coordinate (rotating it by -/theta/ around z 
-axis). Then, for the polar symmetric smear
+**[Equation 10]**
+
+Since the weighting factor on each of the bins is known, it is convenient to
+transform *x'-y'* back to *x-y* coordinates (by rotating it by -|theta| around the
+*z* axis).
+
+Then, for a polar symmetric smear
 
 .. image:: sm_image025.gif
 
-Equation 11
+**[Equation 11]**
 
 where
@@ -186,9 +201,9 @@
 .. image:: sm_image026.gif
 
-while for the x-y symmetric smear
+while for a *x-y* symmetric smear
 
 .. image:: sm_image027.gif
 
-Equation 12
+**[Equation 12]**
 
 where
@@ -196,10 +211,19 @@
 .. image:: sm_image028.gif
 
-Here, the current version of the SasView uses Equation 11 for 2D smearing 
-assuming that all the Gaussian weighting functions are aligned in the polar 
-coordinate.
-
-In the control panel, the higher accuracy indicates more and finer binnng 
-points so that it costs more in time.
-
-.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
+The current version of the SasView uses Equation 11 for 2D smearing, assuming
+that all the Gaussian weighting functions are aligned in the polar coordinate.
+
+.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
+
+Weighting & Normalization
+-------------------------
+
+In all the cases above, the weighting matrix *W* is calculated on the first call
+to a smearing function, and includes ~60 *q* values (finely and evenly binned)
+below (>0) and above the *q* range of data in order to smear all data points for
+a given model and slit/pinhole size. The *Norm*  factor is found numerically with the
+weighting matrix and applied on the computation of *I*\ :sub:`s`.
+
+.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
+
+.. note::  This help document was last changed by Steve King, 01May2015
