U.S. Universities’ Net Returns from Patenting and Licensing: A Quantile Regression Analysis, September 2006

In line with the rights and incentives provided by the Bayh-Dole Act of 1980, U.S. universities have increased their involvement in patenting and licensing activities through their own technology transfer offices. Only a few U.S. universities are obtaining large returns, however, whereas others are continuing with these activities despite negligible or negative returns. We assess the U.S. universities’ potential to generate returns from licensing activities by modeling and estimating quantiles of the distribution of net licensing returns conditional on some of their structural characteristics. We find limited prospects for public universities without a medical school everywhere in their distribution. Other groups of universities (private, and public with a medical school) can expect significant but still fairly modest returns only beyond the 0.9th quantile. These findings call into question the appropriateness of the revenue-generating motive for the aggressive rate of patenting and licensing by U.S. universities.

Review of Cold In-Place Recycled Asphalt Concrete Projects, HR-392, 1998

Highway Research Project HR-392 was undertaken to evaluate cold in-place asphalt recycled (CIR) projects in the State of Iowa. The research involved assessment of performance levels, investigation of factors that most influence pavement performance and economy, and development of guidelines for CIR project selection. The performance was evaluated in two ways: Pavement Condition Indices (PCI, U.S. Corps of Engineers) were calculated and overall ratings were given on ride and appearance. A regression analysis was extrapolated to predict the future service life of CIR roads. The results were that CIR roads within the State of Iowa, with less than 2000 annual average daily traffic (AADT), have an average predicted service life of fifteen to twenty-six years. Subgrade stability problems can prevent a CIR project from being successfully constructed. A series of Dynamic Cone Penetrometer (DCP) tests were conducted on a CIR project that experienced varying levels of subgrade failure during construction. Based on this case study, and supporting data, it was determined that the DCP test can be used to evaluate subgrades that have insufficient stability for recycling. Overall, CIR roads in Iowa are performing well. It appears that the development of transverse cracking has been retarded and little rutting has occurred. Contracting agencies must pay special attention to the subgrade conditions during project selection. Because of its performance, CIR is a recommended method to be considered for rehabilitating aged low volume (<2000 AADT) asphalt concrete roads in Iowa.

Techniques for Estimating Flood-Frequency Discharges for Streams in Iowa, HR-395A, 2001

A statewide study was conducted to develop regression equations for estimating flood-frequency discharges for ungaged stream sites in Iowa. Thirty-eight selected basin characteristics were quantified and flood-frequency analyses were computed for 291 streamflow-gaging stations in Iowa and adjacent States. A generalized-skew-coefficient analysis was conducted to determine whether generalized skew coefficients could be improved for Iowa. Station skew coefficients were computed for 239 gaging stations in Iowa and adjacent States, and an isoline map of generalized-skew-coefficient values was developed for Iowa using variogram modeling and kriging methods. The skew map provided the lowest mean square error for the generalized-skew- coefficient analysis and was used to revise generalized skew coefficients for flood-frequency analyses for gaging stations in Iowa. Regional regression analysis, using generalized least-squares regression and data from 241 gaging stations, was used to develop equations for three hydrologic regions defined for the State. The regression equations can be used to estimate flood discharges that have recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years for ungaged stream sites in Iowa. One-variable equations were developed for each of the three regions and multi-variable equations were developed for two of the regions. Two sets of equations are presented for two of the regions because one-variable equations are considered easy for users to apply and the predictive accuracies of multi-variable equations are greater. Standard error of prediction for the one-variable equations ranges from about 34 to 45 percent and for the multi-variable equations range from about 31 to 42 percent. A region-of-influence regression method was also investigated for estimating flood-frequency discharges for ungaged stream sites in Iowa. A comparison of regional and region-of-influence regression methods, based on ease of application and root mean square errors, determined the regional regression method to be the better estimation method for Iowa. Techniques for estimating flood-frequency discharges for streams in Iowa are presented for determining ( 1) regional regression estimates for ungaged sites on ungaged streams; (2) weighted estimates for gaged sites; and (3) weighted estimates for ungaged sites on gaged streams. The technique for determining regional regression estimates for ungaged sites on ungaged streams requires determining which of four possible examples applies to the location of the stream site and its basin. Illustrations for determining which example applies to an ungaged stream site and for applying both the one-variable and multi-variable regression equations are provided for the estimation techniques.

Investigation of Electromagnetic Gauges for Determination of In-Place Density of HMA Pavements, TR-576, 2009

This study evaluated the use of electromagnetic gauges to determine the adjusted densities of HMA pavements. Field measurements were taken with two electromagnetic gauges, the Pavement Quality Indicator (PQI) 301 and the Pavetracker Plus 2701B. Seven projects were included in the study with 3 to 5 consecutive paving days. For each day/lot 20 randomly selected locations were tested along with seven core locations. The analysis of PaveTracker and PQI density consisted of determining which factors are statistically significant, and core density residuals and a regression analysis of core as a function of PaveTracker and PQI readings. The following key conclusions can be stated: 1. Core density, traffic and binder content were all found to be significant for both electromagnetic gauges studied, 2. Core density residuals are normally distributed and centered at zero for both electromagnetic gauges, 3. For PaveTracker readings, statistically one third of the lots do not have an intercept that is zero and two thirds of the lots do not rule out a scaler correction factor of zero, 4. For PQI readings, statistically the 95% confidence interval rules out the intercept being zero for all seven projects and six of the seven projects do not rule out the scaler correction factor being zero, 5. The PQI 301 gauge should not be used for quality control or quality assurance, and 6. The Pavetracker 2701B gauge can be used for quality control but not quality assurance. This study has found that with the limited sample size, the adjusted density equations for both electromagnetic gauges were determined to be inadequate. The PaveTracker Plus 2701B was determined to be better than the PQI 301. The PaveTracker 2701B could still be applicable for quality assurance if the number of core locations per day is reduced and supplemented with additional PaveTracker 2701B readings. Further research should be done to determine the minimum number of core locations to calibrate the gauges each day/lot and the number of additional PaveTracker 2701B readings required.

Methods for Estimating Annual Exceedance-Probability Discharges for Streams in Iowa, Based on Data through Water Year 2010, TR-519, 2013

A statewide study was performed to develop regional regression equations for estimating selected annual exceedance- probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedanceprobability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized leastsquares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized leastsquares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.