Enhancements to Procedure for Estimating ESALs

Kentucky\u27s current procedure for estimating equivalent single axle loads (ESALs) was updated in 1990 to incorporate traffic data categorized by functional class rather than by statewide averages. This change resulted from the influx of data generated by automatic equipment used to classify and weigh vehicles in motion. A much wider range of geographic conditions and road conditions was sampled, and the expectation was that the data used in the estimation procedure would be more accurate as a result. The 1990 revisions were quite extensive, and, although model calibrations using 1989 and 1990 data have proven useful, the Division of Planning has sought refinements which would improve the calibrations and make them more useful for specific needs. In addition, the continuing analysis of weight and classification data for coal trucks has identified potential improvements that could produce more representative data for these types of vehicles. In response to these needs, a research study was proposed for FY 1992 with funds totaling $25,000 (Appendix A). Funding limitations delayed the study until FY 1993 and reduced the amount to$15,000. Although there was some decrease in scope, the study has been successful in 1) enhancing the accuracy of the calibration process; 2) improving the appearance, clarity, and utility of the output; and 3) potentially reducing year-to-year variations in the estimation of key quantities. In addition, a possible revision has been outlined which would eventually offer other benefits including a more definitive and accurate method for reflecting effects of coal movement. The purpose of this report is to explain and document the progress that has been made toward improving the ESAL-estimation process and exploiting the wealth of data being generated by the new vehicle classification and weighing program

Equivalent Single Axleload Computer Program Enhancements

The objectives of the study were to review and modify previously used Equivalent Single Axleload (ESAL) prediction procedures and to develop a more efficient procedure. As part of the effort to simplify the procedure, a subtask was undertaken to reduce the number of highway functional classes being used to process data for the ESAL estimation procedure. Another objective was to develop a more definitive and accurate method for reflecting the effects of coal or heavy truck movements. Results of this task were documented as Research Report KTC-95-6. Analyses were performed and validated to reduce the twelve functional classes to six aggregate categories. The overall ESAL estimating process, which was previously accomplished using mainframe computer programs, was converted to microcomputer/PC programs and documented in detail. A procedure for processing ESAL data by aggregate classes was documented and example output was presented. An analysis was performed to determine the reliability of traffic parameter estimates used in the ESAL estimating process. Results were produced to identify the number of volume, classification and weigh-in-motion stations required to adequately define the traffic characteristics of a specific functional or aggregate class

Update of Data for Estimating ESALs

This project involved updating processing traffic characteristics data using a series of quality control and analytical programs to produce an estimate of the following parameters of interest; 1) average daily traffic, 2) percent trucks, 3) percent trucks classified as heavy/coal, 4) axles per truck, 5) axles per heavy/coal truck, 6) ESALs per truck axle, 7) ESALs per heavy/coal truck axle, and 8) total ESALs. ESAL estimation parameters used WIM data collected during 2007, 2011, and 2012–2013 (representing 41 stations); and classification data collected in 2010, 2011 and 2012 (representing 1,669 stations). Computer programs used to process classification data, process weight data, and then combining output to calculate ESALs are contained in the three following programs; 1) CLASS SUMMARY – processes vehicle classification data and produces annual average number of vehicle types at each classification station, 2) LOADOMTR SUMMARY – processes truck weight data to produce axle load distributions by vehicle type, and 3) AGGCALC – processes output form LOADOMTR AND CLASS programs to produce ESAL-related parameters of interest. A flowchart which provides steps of processing data and calculating estimates of ESALs is included in Appendix A and computer code for each of these programs is included in Appendix B

An evolutionary history of defensins: a role for copy number variation in maximizing host innate and adaptive immune responses

Defensins represent an evolutionary ancient family of antimicrobial peptides that play diverse roles in human health and disease. Defensins are cationic cysteine-containing multifunctional peptides predominantly expressed by epithelial cells or neutrophils. Defensins play a key role in host innate immune responses to infection and, in addition to their classically described role as antimicrobial peptides, have also been implicated in immune modulation, fertility, development, and wound healing. Aberrant expression of defensins is important in a number of inflammatory diseases as well as modulating host immune responses to bacteria, unicellular pathogens, and viruses. In parallel with their role in immunity, in other species, defensins have evolved alternative functions, including the control of coat color in dogs. Defensin genes reside in complex genomic regions that are prone to structural variations and some defensin family members exhibit copy number variation (CNV). Structural variations have mediated, and continue to influence, the diversification and expression of defensin family members. This review highlights the work currently being done to better understand the genomic architecture of the β-defensin locus. It evaluates current evidence linking defensin CNV to autoimmune disease (i.e., Crohn’s disease and psoriasis) as well as the contribution CNV has in influencing immune responses to HIV infection

BuildUp

Lists high crash locations throughout the state [Kentucky]

Annual Update of Data for Estimating ESALS

A revised procedure for estimating equivalent single axleloads (ESAL’s) was developed in 1985. This procedure used weight, classification, and traffic volume data collected by the Transportation Cabinet’s Division of Planning. The procedure was developed and documented as Research Report UKTRP-85-30, and was titled “Estimation of Equivalent Axleloads”. Since the revised procedure was adopted, there have been several changes; the most recent being documented as Report KTC-95-7 titled “Equivalent Single Axleload Computer Program Enhancements”. Results documented in Report KTC-95-7 included improvements in the processing of ESAL data by aggregation of the functional classes to increase the accuracy of the estimates within a class, and conversion of computer programs used to process the data from mainframe to personal computer

Development of Procedures for Identifying High-Crash Locations and Prioritizing Safety Improvements

The objectives of this study were to review and analyze the current procedures for identifying high-crash locations and evaluating and prioritizing roadway safety improvements at high-crash locations, and to recommend improved methods. Several tasks were undertaken to accomplish these objectives, including the following: Review of program guidelines and procedures used by other states to prioritize improvements at high-crash locations Review and documentation of Kentucky’s current procedures Update of Kentucky’s Crash Buildup Program software to be compatible with the 2000 crash report form Development of new software to assist in estimating the benefits and costs of potential projects for inclusion in the Hazard Elimination Program Conversion of the dynamic programming software from mainframe to PC Results from the study include improved methods for identifying high-frequency crash locations and prioritizing those locations after preliminary analyses indicated a need to consider improvements at a crash site. Software was developed to produce a generalized estimate of the benefits and costs of potential projects for inclusion in the Hazard Elimination Program. Features included the following: 1) a menu of types of improvement projects and related reduction factors; 2) algorithms for calculating the present worth of annual benefits from crash reductions; and 3) benefit-cost comparisons for each project. The user must enter an estimate of project costs in order to estimate the benefit-cost ratio for the proposed improvement at a highway segment. Revisions were recommended for updating and enhancing the Crash Buildup Program to achieve compatibility with the current crash data report form and for translating the dynamic programming module from a mainframe operation to a PC-based system. It appears that an increased level of functionality has been achieved as a result of the series of modifications and improvements

Development of Procedures for Identifying High-Crash Locations and Prioritizing Safety Improvements

The objectives of this study were to review and analyze the current procedures for identifying high-crash locations and evaluating and prioritizing roadway safety improvements at high-crash locations, and to recommend improved methods. Several tasks were undertaken to accomplish these objectives, including the following: Review of program guidelines and procedures used by other states to prioritize improvements at high-crash locations Review and documentation of Kentucky’s current procedures Update of Kentucky’s Crash Buildup Program software to be compatible with the 2000 crash report form Development of new software to assist in estimating the benefits and costs of potential projects for inclusion in the Hazard Elimination Program Conversion of the dynamic programming software from mainframe to PC Results from the study include improved methods for identifying high-frequency crash locations and prioritizing those locations after preliminary analyses indicated a need to consider improvements at a crash site. Software was developed to produce a generalized estimate of the benefits and costs of potential projects for inclusion in the Hazard Elimination Program. Features included the following: 1) a menu of types of improvement projects and related reduction factors; 2) algorithms for calculating the present worth of annual benefits from crash reductions; and 3) benefit-cost comparisons for each project. The user must enter an estimate of project costs in order to estimate the benefit-cost ratio for the proposed improvement at a highway segment. Revisions were recommended for updating and enhancing the Crash Buildup Program to achieve compatibility with the current crash data report form and for translating the dynamic programming module from a mainframe operation to a PC-based system. It appears that an increased level of functionality has been achieved as a result of the series of modifications and improvements