End of Life Conversations, October 2003

A short course designed for adult study groups Prepared by the Curriculum Task Force of the End-of-Life Care Coalition of Central Iowa

Farm-Level Analysis of Risk Management Proposals, March 2000

This paper presents a detailed report of the representative farm analysis (summarized in FAPRI Policy Working Paper #01-00). At the request of several members of the Committee on Agriculture, Nutrition, and Forestry of the U.S. Senate, we have continued to analyze the impacts of the Farmers’ Risk Management Act of 1999 (S. 1666) and the Risk Management for the 21st Century Act (S. 1580). Earlier analysis reported in FAPRI Policy Working Paper #04-99 concentrated on the aggregate net farm income and government outlay impacts. The representative farm analysis is conducted for several types of farms, including both irrigated and non-irrigated cotton farms in Tom Green County, Texas; dryland wheat farms in Morton County, North Dakota and Sumner County, Kansas; and a corn farm in Webster County, Iowa. We consider additional factors that may shed light on the differential impacts of the two plans. 1. Farm-level income impacts under alternative weather scenarios. 2. Additional indirect impacts, such as a change in ability to obtain financing. 3. Implications of within-year price shocks. Our results indicate that farmers who buy crop insurance will increase their coverage levels under S. 1580. Farmers with high yield risk find that the 65 percent coverage level maximizes expected returns, but some who feel that they obtain other benefits from higher coverage will find that the S. 1580 subsidy schedule significantly lowers the cost of obtaining the additional coverage. Farmers with lower yield risk find that the increased indemnities from additional coverage will more than offset the increase in producer premium. In addition, because S. 1580 extends its increased premium subsidy percentages to revenue insurance products, farmers will have an increased incentive to buy revenue insurance. Differences in the ancillary benefits from crop insurance under the baseline and S. 1580 would be driven by the increase in insurance participation and buy-up. Given the same levels of insurance participation and buy-up, the ancillary benefits under the two scenarios would be the same.

Artificial-Intelligence-Based Optimization of the Management of Snow Removal Assets and Resources Final Report, October 2002

Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent snow removal asset management system (SRAMS). The system has been evaluated through a case study examining snow removal from the roads in Black Hawk County, Iowa, for which the Iowa Department of Transportation (Iowa DOT) is responsible. The SRAMS is comprised of an expert system that contains the logical rules and expertise of the Iowa DOT’s snow removal experts in Black Hawk County, and a geographic information system to access and manage road data. The system is implemented on a mid-range PC by integrating MapObjects 2.1 (a GIS package), Visual Rule Studio 2.2 (an AI shell), and Visual Basic 6.0 (a programming tool). The system could efficiently be used to generate prioritized snowplowing routes in visual format, to optimize the allocation of assets for plowing, and to track materials (e.g., salt and sand). A test of the system reveals an improvement in snowplowing time by 1.9 percent for moderate snowfall and 9.7 percent for snowstorm conditions over the current manual system.

End of Project Report to the Iowa Power Fund, October 31, 2008

The 2008 Biobased Industry Outlook Conference was held September 7-10 on the Iowa State University campus. Over 750 people attended the plenary sessions on the morning of September 8th; 580 people registered for the full conference. Sponsorships: $92,500 in sponsorships in addition to the IPF was secured for the conference (considered “match” to the IPF grant). Including the $11,250 IPF sponsorship ($12,500 minus overhead charges of $1,250), the total amount contributed for conference sponsorships was $103,750. A list of sponsors and the amount of sponsorship is listed in Appendix A. Sponsorship funds received from the Iowa Power Fund were used for supplies and materials. Please see Appendix B which documents the transfer of IPF grant funds internally at ISU and their use.

Field Evaluation of Quality Management Concrete, MLR-97-3, 1998

Quality management concrete allows the contractor to develop the mix design for the portland cement concrete. This research was initiated to gain knowledge about contractor mix designs. An experiment was done to determine the variation in cylinders, beams, and cores that could be used to test the strength of the contractor's mix. In addition, the contractor's cylinder strengths and gradations were analyzed for statistical stability and process capability. This research supports the following conclusions: (1) The mold type used to cast the concrete cylinders had an effect on the compressive strength of the concrete. The 4.5-in. by 9-in. (11.43-cm by 22.86-cm) cylinders had lower strength at a 95% confidence interval than the 4-in. by 8-in. (10.16-cm by 20.32-cm) and 6-in. by 12-in. (15.24-cm by 30.48-cm) cylinders. (2) The low vibration consolidation effort had the lowest strength of the three consolidation efforts. In particular, an interaction occurred between the low vibration effort and the 4.5-in. by 9-in. (11.43-cm by 22.86-cm) mold. This interaction produced very low compressive strengths when compared with the other consolidation efforts. (3) A correlation of 0.64 R-squared was found between the 28 day cylinder and 28 day compressive strengths. (4) The compressive strength results of the process control testing were not in statistical control. The aggregate gradations were mostly in statistical control. The gradation process was capable of meeting specification requirements. However, many of the sieves were off target. (5) The fineness modulus of the aggregate gradations did not correlate well with the strength of the concrete. However, this is not surprising considering that the gradation tests and the strength tests did not represent the same material. In addition, the concrete still has many other variables that will affect its strength that were not controlled.