NASA/CR-2014-218393 

Transition Marshall Space Flight Center 

Wind Profiler Splicing Algorithm to Launch 

Services Program Upper Winds Tool 

William H. Bauman III 

ENSCO, Inc., Cocoa Beach, Florida 

NASA Applied Meteorology Unit, Kennedy Space Center, Florida 

August 2014 
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NASA/CR-2014-218393 

Transition Marshall Space Flight Center 

Wind Profiler Splicing Algorithm to Launch 

Services Program Upper Winds Tool 

William H. Bauman III 

ENSCO, Inc., Cocoa Beach, Florida 

NASA Applied Meteorology Unit, Kennedy Space Center, Florida 

National Aeronautics and 

Space Administration 

Kennedy Space Center 

Kennedy Space Center, FL 32899-0001 

August 2014 
Acknowledgements

The author wishes to thank Mr. Barbré of the Jacobs Engineering and Science Services and Skills 

Augmentation Group at the Marshall Space Flight Center Natural Environments Branch, who 

developed the splicing algorithms. Mr. Barbré provided his expertise and guidance in helping the 

Applied Meteorology Unit transition the algorithms he wrote in MATLAB® software into Microsoft®

Excel® Visual Basic for Applications for implementation in the LSP Upper Winds tool. 

Available from: 

NASA Center for AeroSpace Information 

7115 Standard Drive 

Hanover, MD 21076-1320 

443-757-5802 

This report is also available in electronic form at 

http://science.ksc.nasa.gov/amu/
2 

Executive Summary 

Customer: NASA’s Launch Services Program (LSP) and Space Launch System (SLS) program 

NASA’s LSP customers and the future SLS program rely on observations of upper-level winds 

for steering, loads, and trajectory calculations for the launch vehicle’s flight. On the day of launch, 

the 45th Weather Squadron (45 WS) Launch Weather Officers (LWOs) monitor the upper-level 

winds and provide forecasts to the launch team via the AMU-developed LSP Upper Winds tool 

for launches at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station. This tool 

displays wind speed and direction profiles from rawinsondes released during launch operations, 

the 45th Space Wing 915-MHz Doppler Radar Wind Profilers (DRWPs) and KSC 50-MHz DRWP, 

and output from numerical weather prediction models. 

The goal of this task was to splice the wind speed and direction profiles from the 45th Space 

Wing (45 SW) 915-MHz Doppler radar Wind Profilers (DRWPs) and KSC 50-MHz DRWP at 

altitudes where the wind profiles overlap to create a smooth profile. In the first version of the LSP 

Upper Winds tool, the top of the 915-MHz DRWP wind profile and the bottom of the 50-MHz 

DRWP were not spliced, sometimes creating a discontinuity in the profile. The Marshall Space 

Flight Center (MSFC) Natural Environments Branch (NE) created algorithms to splice the wind 

profiles from the two sensors to generate an archive of vertically complete wind profiles for the 

SLS program. The AMU worked with MSFC NE personnel to implement these algorithms in the 

LSP Upper Winds tool to provide a continuous spliced wind profile. 

The AMU transitioned the MSFC NE algorithms to interpolate and fill data gaps in the data, 

implement a Gaussian weighting function to produce 50-m altitude intervals in each sensor, and 

splice the data together from both DRWPs. They did so by porting the MSFC NE code written 

with MATLAB® software into Microsoft® Excel® Visual Basic for Applications (VBA). After testing 

the new algorithms in stand-alone VBA modules, the AMU replaced the existing VBA code in the 

LSP Upper Winds tool with the new algorithms. They then tested the code in the LSP Upper 

Winds tool with archived data. The tool will be delivered to the 45 WS after the 50-MHz DRWP 

upgrade is complete and the tool is tested with real-time data. The 50-MHz DRWP upgrade is 

expected to be finished in October 2014. 
3 

Table of Contents

Executive Summary .................................................................................................................... 2

List of Figures ............................................................................................................................. 4

1. Introduction ........................................................................................................................... 5

2. Data Analysis ........................................................................................................................ 5

2.1 Data Gap-filling ............................................................................................................. 5

2.2 Interpolating to 50-m Altitudes ...................................................................................... 8

2.3 Weighting Scheme for Splicing ................................................................................... 10

3. Updating the LSP Upper Winds Tool ................................................................................... 13

4. Summary............................................................................................................................. 14
4 

List of Figures 

Figure 1. RMS component difference from the measured wind (ms-1) as a function of data gap 

size (m) for the 50-MHz DRWP (green line) and the 915-MHz DRWP (blue line). The 

analysis uses the thresholds to determine how many consecutive gaps to tolerate 

when splicing 50- and 915-MHz DRWP profiles. Figure B2.3 from Barbré (2013). .. 6

Figure 2. Excel spreadsheets showing observed (a) and gap-filled (b) data from 915-MHz 

DRWP data. ............................................................................................................ 7

Figure 3. Chart showing observed wind speed (red lines) and gap-filled interpolated wind speed 

(blue lines) from the 915-MHz DRWP for 1516 UTC 2 January 2014. ..................... 8

Figure 4. Chart showing 145-m observed wind speed (red line) and 50-m interpolated wind 

speed (blue line) from the 50-MHz DRWP for 1515 UTC 2 January 2014. .............. 9

Figure 5. Chart showing 101-m observed wind speed (red line) and 50-m interpolated wind 

speed (blue line) from the 9150-MHz DRWP for 1516 UTC 2 January 2014. .........10

Figure 6. Results after applying the MATLAB Gaussian weighting function to the 31 overlapping 

altitudes from the 31 concurrent 915-MHz and 50-MHz DRWP profiles. The x- and yaxes denote the number of overlapping altitudes (L) and the weight (w; 

dimensionless), respectively. ..................................................................................11

Figure 7. Normalized wn(z) values used to compute the spliced DRWP wind components for 

the overlapping altitude region extending from 2,666 to 4,117 m. The x- and y-axes 

denote the weight (w; dimensionless) and altitude (m), respectively. ......................11

Figure 8. Example wind speed profile versus altitude (m) for 1515 UTC 2 January 2014. Red, 

green, and black lines stand for the concurrent 915-MHz, 50-MHz, and spliced DRWP 

profiles, respectively. ..............................................................................................12

Figure 9. Example wind direction profile versus altitude (m) for 1515 UTC 2 January 2014. Red, 

green, and black lines stand for the concurrent 915-MHz, 50-MHz, and spliced DRWP 

profiles, respectively. ..............................................................................................12

Figure 10. Spliced wind speed (left) and wind direction (right) from concurrent 915-MHz (orange 

line) and 50-MHz (red line) DRWPs as displayed in the LSP Upper Winds tool. .....13
5 

1. Introduction 

NASA’s Launch Services Program (LSP) customers and the future Space Launch System 

(SLS) program rely on observations of upper-level winds for steering, loads, and trajectory 

calculations for the launch vehicle’s flight. On the day-of-launch, the 45th Weather Squadron (45 

WS) launch weather officers (LWOs) monitor the upper-level winds and provide forecasts to the 

launch team management via the AMU-developed LSP Upper Winds tool (Bauman and Wheeler 

2012) for launches at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station. This 

tool displays wind speed and direction profiles from rawinsondes released during launch 

operations, the 45th Space Wing 915-MHz Doppler Radar Wind Profilers (DRWPs) and KSC 50-

MHz DRWP, and output from numerical weather prediction models. 

The rawinsondes and models provide continuous profiles from the surface to over 60,000 ft, 

while the DRWPs do not. The 915-MHz DRWPs measure the winds at altitudes ranging from 285 

to 14,560 ft (87–4,438 m) while the 50-MHz DRWP measures winds at altitudes ranging from 

8,747 to 61,024 ft (2,700–18,600 m). Even though the nominal altitudes of these sensor’s 

measurements overlap at the top of the 915-MHz DRWPs and bottom of the 50-MHz DRWP, the 

wind speeds and directions do not necessarily match at that interface. To compensate for this 

variation, the Marshall Space Flight Center (MSFC) Natural Environments Branch (NE) developed 

algorithms to splice concurrent measurements from both profilers. 

The LSP Upper Winds tool uses both DRWP sources to create a continuous profile of winds 

from approximately 427 to 61,024 ft (130–18,600 m). In the original LSP Upper Winds tool, the 

915-MHz DRWP wind profile was cut off to match the bottom altitude of the 50-MHz DRWP wind 

profile or the wind profiles were connected via a straight line interpolation from the top of the 915-

MHz data to the bottom of the 50-MHz data. The straight line interpolation was implemented due 

to time constraints levied on the task but it does not provide the smoothed profile that can be 

realized by splicing the data together among overlapping altitudes from both sensors. This report 

describes how the AMU transitioned the MSFC NE algorithms for interpolating and splicing the 

data from the 915-MHz and 50-MHz DRWPs into the existing LSP Upper Winds Tool. 

The MSFC NE splicing technique was developed using functions available in the MATLAB®

software. Since the LSP Upper Winds tool was written in Microsoft® Excel® using Visual Basic for 

Applications (VBA), the AMU manually recreated the MATLAB functions in VBA. 

2. Data Analysis 

The preprocessing performed on individual 915- and 50-MHz DRWP profiles before splicing 

entails filling data gaps in the original profile and then interpolating the data from both sensors to 

50-m altitudes. This section describes the processes needed to get to a complete spliced wind 

profile. 

2.1 Data Gap-filling 

MSFC NE performed an analysis that quantified the maximum tolerable data gap size from 

the 50- and 915-MHz DRWP profiles (Barbré 2013). Figure 1 shows the root mean square (RMS) 

of the maximum wind component differences versus gap size for each sensor. The analysis 

compared these results with a selected threshold of 1.0 ms-1 RMS, which is the 50-MHz DRWP 

acceptable measurement error (Pinter et al. 2006). No such quantification exists for the 915-MHz 

measurement error, but the NASA meteorological community considers the 915-MHz DRWP 

errors to resemble the 50-MHz DRWP errors (Barbré 2013). MSFC NE used the largest gap size 

that did not exceed the threshold as the criteria. Figure 1 depicts the gap sizes as 300 m for the 

50-MHz DRWP analysis and 500 m for the 915-MHz DRWP analysis. 
6 

The 50-MHz DRWP reports observations at 145-m altitude intervals while the 915-MHz 

DRWP reports observations at 101-m altitude intervals. For the 50-MHz DRWP, the AMU wrote 

VBA code to fill data gaps ≤ 290 m by linearly interpolating the wind components through the gap. 

For the 915-MHz DRWP, they wrote VBA code to fill data gaps ≤ 505 m by linearly interpolating 

the wind components through the gap. The AMU chose these values instead of 300 and 500 m 

because they are multiples of the DRWP altitude intervals. 

Figure 1. RMS component difference from the measured wind 

(ms-1) as a function of data gap size (m) for the 50-MHz DRWP 

(green line) and the 915-MHz DRWP (blue line). The analysis 

uses the thresholds to determine how many consecutive gaps 

to tolerate when splicing 50- and 915-MHz DRWP profiles. 

Figure B2.3 from Barbré (2013). 

Figure 2 demonstrates how the gap-filling algorithm works on a 915-MHz DRWP profile using 

data from 1516 UTC 2 January 2014. Figure 2a shows a portion of the Excel spreadsheet 

containing the observed data from a 915-MHz profile before gap-filling. The VBA code imports 

the raw data file in ASCII text format, reformats it into three columns containing altitude, wind 

direction, and wind speed, and then calculates u- and v-wind components in the fourth and fifth 

columns. The code flags missing data by changing the format of the altitude values to red, bold 

text and by changing missing values of “-9999” to empty cells. Once this is complete, another 

VBA macro looks for consecutive empty cells in the wind direction column to determine if and how 

the gap should be filled. If five or more consecutive empty cells are identified by the code, the 

profile is truncated at the highest altitude before reaching the first of the five empty cells. In Figure 

2a, this condition was met above 4,177 m, so the profile was truncated at this altitude as shown 

in the resulting gap-filled data in Figure 2b. Missing data were also found at 2,558 m and between 

2,761 m and 3,166 m. Since both of these gaps were ≤ 505 m, the code performed a linear 

interpolation of the observed data through the gap. The code interpolates the u- and v-wind 

components above and below the gap, inserts the interpolated results in the u-wind and v-wind 

columns at the appropriate altitudes as depicted in Figure 2b and then calculates wind direction 

and wind speed at each altitude resulting in a continuous vertical wind profile. 

A chart of the observed and gap-filled data from the 1516 UTC 2 January 2014 915-MHz 

DRWP is shown in Figure 3. The red lines are plots of the observed wind speed derived from data 
7 

in the third column (Speed (kt)) in Figure 2a. The blue lines plots of the gap-filled interpolated 

wind speed derived from the data in third column (Speed (kt)) in Figure 2b. The gap-filling 

algorithm works in the same manner for the 50-MHz DRWP data. After the gap-filling process is 

complete for both sensors, the data are interpolated to 50-m altitudes. 

 

Figure 2. Excel spreadsheets showing observed (a) and gap-filled (b) data from 

915-MHz DRWP data. 
8 

Figure 3. Chart showing observed wind speed (red lines) and gap-filled 

interpolated wind speed (blue lines) from the 915-MHz DRWP for 1516 

UTC 2 January 2014. 

2.2 Interpolating to 50-m Altitudes 

MSFC NE used a MATLAB function called interp1 to interpolate the 915-MHz and 50-MHz 

observations from 101 m and 145 m, respectively, to 50-m altitude intervals. Since the AMU did 

not have a copy of MATLAB and the LSP Upper Winds tool was developed in Excel, Mr. Barbré 

from MSFC NE outlined how the function worked so the AMU could write the code in VBA. 

Creating the algorithm required computing a weighted value, w, for each observed and 

interpolated altitude, and applying w to the u- and v-wind components at each interpolated 50-m 

altitude. The VBA code computes w by finding the highest altitude (zblw) that is below the altitude 

of interest, zi, and the lowest altitude (zabv) that is above the altitude of interest, zi, using all the 

observed 101-m (915-MHz DRWP) and 145-m (50-MHz DRWP) interval altitudes, z. The 

equations for these quantities are 

zblw = max (z (z ≤ zi)) 

zabv = min (z (z ≥ zi)) 

w = (zi - zblw) / (zabv - zblw). If zabv = zblw then w = 1. 

For example, for the 50-MHz DRWP, given altitudes at z = 2,666 m and 2,811 m, zi would 

include altitudes at 2,666 m, 2,716 m, and 2,766 m, resulting in three values for w at each zi. 

w at zi = 2,666: 

zblw = max ([2,666 ≤ 2,666]) = 2,666

zabv = min ([2,666 ≥ 2,666, 2,811, 2,956, 3,101...]) = 2,666

w = 1 since zabv = zblw

w at zi = 2,716: 

zblw = max ([2,666, 2,811, 2,956... ≤ 2,716]) = 2,666

zabv = min ([2,666, 2,811, 2,956... ≥ 2,716]) = 2,811
9 

w = (2,716-2,666)/(2,811-2,666) = 0.34483 

w at zi = 2,766: 

zblw = max ([2,666, 2,811, 2,956... ≤ 2,766]) = 2,666

zabv = min ([2,666, 2,811, 2,956... ≥ 2,766]) = 2,811

w = (2,766-2,666)/(2,811-2,666) = 0.68966

To compute the u-component at each interpolated altitude, ui, use the equation: 

ui = (1-w) * u (zblw) + w * (zabv)

Therefore, if u = 6.8 kt at 2,666 m and u = 7.9 kt at 2,811 m, the u-components at the 

interpolated altitudes are: 

At 2,666 m: 

u2666 = (1-1) * 6.8 + 1 * 6.8 = 6.8 kt

At 2,716 m: 

u2716 = (1-0.34483) * 6.8 + 0.34483 * 7.9 = 7.2 kt

At 2,766 m: 

u2766 = (1-0.68966) * 6.8 + 0.68966 * 7.9 = 7.6 kt

The interpolation algorithm was applied to 50-MHz DRWP and 915-MHz DRWP profiles as 

shown in Figure 4 and Figure 5. Figure 4 shows a 50-MHz wind speed profile from 1515 UTC 2 

January 2014 with data plotted at 145-m (observed) and 50-m (interpolated) altitude intervals and 

Figure 5 shows a 915-MHz wind speed profile from 1516 UTC 2 January 2014 with data plotted 

at 101-m (observed) and 50-m (interpolated) altitude intervals. 

Figure 4. Chart showing 145-m observed wind speed (red line) and 

50-m interpolated wind speed (blue line) from the 50-MHz DRWP for 1515 

UTC 2 January 2014. 
10 

Figure 5. Chart showing 101-m observed wind speed (red line) and 

50-m interpolated wind speed (blue line) from the 9150-MHz DRWP for 

1516 UTC 2 January 2014. 

2.3 Weighting Scheme for Splicing 

Once the 915-MHz and 50-MHz DRWPs winds were interpolated to 50-m intervals, MSFC NE 

used the MATLAB function gausswin as a Gaussian weighting function to determine which profiler 

had more influence on the resulting wind component values at each height. This function, w(z), is 

defined by the equation: 

ݓሺݖሻ ൌ ݁ିଵ

ଶቆఈ ௡

ே

ଶൗ ቇ

మ

Where: 

α = 2.5 (MathWorks 2014) 

N = L-1 where L is the number of overlapping altitudes from both DRWPs 

n = (0:N)-N/2

The AMU ported this equation to Excel and tested it with the 31 overlapping altitudes from 

2,666 m to 4,117 m from both DRWPs on 2 January 2014 at 1515 UTC and 1516 UTC. The 

resulting Gaussian distribution of w(z) is shown in Figure 6. The cumulative sum of w is 

normalized by its maximum to produce the chart in Figure 7, which is a plot of the weights used 

to compute the spliced wind components at the 31 altitudes where the 915-MHz DRWP profile 

overlaps the 50-MHz DRWP profile. In this case, w starts at 0.0 at 2,666 m, transitions from 0.0-

1.0 from 2,666 to 4,117 m, and remains at 1.0 above 4,117 m. 
11 

Figure 6. Results after applying the MATLAB Gaussian weighting 

function to the 31 overlapping altitudes from 915-MHz and 50-MHz DRWP 

profiles. The x- and y-axes denote the number of overlapping altitudes (L) 

and the weight (w; dimensionless), respectively. 

To compute the spliced DRWP wind components, the AMU used Equation (12) from Barbré 

(2013) for the u- and v-components, where wn(z) is the normalized weight shown in Figure 7: 

u(z) = wn(z) * u50(z) + [1 – wn(z)] * u915(z)

v(z) = wn(z) * v50(z) + [1 – wn(z)] * v915(z)

Figure 7. Normalized wn(z) values used to compute the spliced DRWP 

wind components for the overlapping altitude region extending from 2,666 

to 4,117 m. The x- and y-axes denote the weight (w; dimensionless) and 

altitude (m), respectively. 

Applying this equation with the appropriate wn at each z produces the spliced profile, which 

fares the 915-MHz DRWP winds into the 50-MHz DRWP winds within the transition region. Figure 

8 shows the spliced wind speed profile and Figure 9 shows the spliced wind direction profile for 
12 

1515 UTC 2 January 2014. Note the spliced profile (black line) significantly resembles the 915-

MHz DRWP profile (red line) below approximately 3,400 m and the 50-MHz DRWP profile (green 

line) above 3,400m, which shows the weighting scheme’s effect.

Figure 8. Example wind speed profile versus altitude (m) for 1515 UTC 2 

January 2014. Red, green, and black lines represent the concurrent 915-

MHz, 50-MHz, and spliced DRWP profiles, respectively. 

Figure 9. Example wind direction profile versus altitude (m) for 1515 UTC 

2 January 2014. Red, green, and black lines represent the concurrent 915-

MHz, 50-MHz, and spliced DRWP profiles, respectively.
13 

3. Updating the LSP Upper Winds Tool 

The final part of this work required porting the new VBA code into the existing LSP Upper 

Winds tool. There are 12 modules in the tool that use data from both wind profilers. Each 

concurrent file from the 50-MHz DRWP and 915-MHz DRWP accessed by the LSP Upper Winds 

tool will need to be checked for missing data using the data gap filling algorithm, interpolated to 

50-m altitude intervals using the interpolation algorithm, and then spliced together using the 

weighting scheme. The AMU copied the VBA code that was developed and tested independent 

of the LSP Upper Winds tool and inserted it in the appropriate modules in the tool. The code was 

modified to work within the framework of the existing code in the tool and then tested on archived 

data. An example of final spliced profiles of wind speed and wind direction from concurrent 915-

MHz and 50-MHz DRWPs are shown in Figure 10. 

Figure 10. Spliced wind speed (left) and wind direction (right) from 

concurrent 915-MHz (orange line) and 50-MHz (red line) DRWPs as 

displayed in the LSP Upper Winds tool. 

During this task, the KSC 50-MHz DRWP was undergoing a complete replacement. Therefore, 

it was not possible to test the LSP Upper Winds Tool with real-time data from the profiler. Once 

the replacement project is completed in late 2014, the AMU will test the LSP Upper Winds tool 

with the real-time data to ensure the newly developed code is working correctly before releasing 

the tool for operational support. 

 
14 

4. Summary 

NASA’s LSP customers and the future SLS program rely on observations of upper-level winds 

for steering, loads, and trajectory calculations for the launch vehicle’s flight. On the day of launch, 

the 45 WS LWOs monitor the upper-level winds and provide forecasts to the launch team via the 

AMU-developed LSP Upper Winds tool for launches at KSC and CCAFS. This tool displays wind 

speed and direction profiles from rawinsondes released during launch operations, the 45 SW 915-

MHz DRWPs and KSC 50-MHz DRWP, and output from numerical weather prediction models. 

The rawinsondes and models provide continuous profiles from the surface to over 60,000 ft, 

while the DRWPs do not. The 915-MHz DRWPs measure the winds at altitudes ranging from 285 

to 14,560 ft (87–4,438 m) while the 50-MHz DRWP measures winds at altitudes ranging from 

8,747 to 61,024 ft (2,700–18,600 m). Even though the nominal altitudes of these sensor’s 

measurements overlap at the top of the 915-MHz DRWPs and bottom of the 50-MHz DRWP, the 

wind speeds and directions do not necessarily match at that interface. To compensate for this 

variation, MSFC NE developed algorithms to splice concurrent measurements from both profilers, 

which the AMU transitioned into the LSP Upper Winds tool to create a smooth profile. 

The AMU transitioned the MSFC NE algorithms to interpolate and fill data gaps in the data, 

implement a Gaussian weighting function to produce 50-m altitude intervals in each sensor, and 

splice the data together from both DRWPs. They did so by porting the MSFC NE code written 

with MATLAB software into Microsoft Excel VBA. After testing the new algorithms in stand-alone 

VBA modules, the AMU replaced the existing VBA code in the LSP Upper Winds tool with the 

new algorithms. They then tested the code in the tool with archived data. The tool will be delivered 

to the 45 WS after the 50-MHz DRWP upgrade is complete and the tool is tested with real-time 

data. The 50-MHz DRWP upgrade is expected to be finished in October 2014. 

 
15 

References

Bauman, W. H. III and M. M. Wheeler, 2012: Assessing Upper-level Winds on Day-of-Launch. 

NASA Contractor Report CR-2012-216313, Kennedy Space Center, FL, 39 pp. [Available 

from ENSCO, Inc., 1980 N. Atlantic Ave., Suite 830, Cocoa Beach, FL 32931 and 

http://science.ksc.nasa.gov/amu/final-reports/lsp-upper-wind-changes.pdf.] 

Barbré, B. J., 2013: Characteristics of the Spliced Kennedy Space Center Doppler RADAR 

Wind Profiler Database. Jacobs ESSSA Group Analysis Report, ESSSA-FY13-1935, 79 

pp. 

MathWorks, 2014: Spectral analysis, Gaussian window function description. [Available online at 

http://www.mathworks.com/help/signal/ref/gausswin.html.] 

Pinter, D. J., F. J. Merceret, and C. V. Hatley, 2006: Performance Validation of Upgraded 

Eastern Range 50-Megahertz Doppler Radar Wind Profiler. J. Spacecr. Rockets, 43, 693–

695. 

 
16 

List of Acronyms 

45 WS 45th Weather Squadron 

45 SW 45th Space Wing 

AMU Applied Meteorology Unit 

DRWP Doppler Radar Wind Profiler 

KSC Kennedy Space Center 

LSP Launch Services Program 

LWO Launch Weather Officer 

MSFC Marshall Space Flight Center 

NE Natural Environments Branch 

SLS Space Launch System 

VBA Visual Basic for Applications 
17 

NOTICE 

Mention of a copyrighted, trademarked or proprietary product, service, or document does not 

constitute endorsement thereof by the author, ENSCO Inc., the AMU, the National Aeronautics 

and Space Administration, or the United States Government. Any such mention is solely for the 

purpose of fully informing the reader of the resources used to conduct the work reported herein.