Climate Change Impacts on Iowa, 2010, January 1, 2011

Today, perhaps without their realization, Iowans are factoring climate change into their lives and activities. Current farming practices and flood mitigation efforts, for example, are reflecting warmer winters, longer growing seasons, warmer nights, higher dew-point temperatures, increased humidity, greater annual stream flows, and more frequent severe precipitation events (Fig. 1) than were prevalent during the past 50 years. Some of the effects of these changes (such as longer growing season) may be positive, while others (particularly the tendency for greater precipitation events that lead to flooding) are negative. Climate change embodies all of these results and many more in a complex manner. The Iowa legislature has been proactive in seeking advice about climate change and its impacts on our state. In 2007, Governor Culver and the Iowa General Assembly enacted Senate File 485 and House File 2571 to create the Iowa Climate Change Advisory Council (ICCAC). ICCAC members reported an emissions inventory and a forecast for Iowa’s greenhouse gases (GHGs), policy options for reducing Iowa’s GHG, and two scenarios charting GHG reductions of 50% and 90% by 2050 from a baseline of 2005. Following issuance of the final report in December 2008, the General Assembly enacted a new bill in 2009 (Sec. 27, Section 473.7, Code 2009 amended) that set in motion a review of climate change impacts and policies in Iowa. This report is the result of that 2009 bill. It continues the dialogue between Iowa’s stakeholders, scientific community, and the state legislature that was begun with these earlier reports.

Iowa Prison Population Forecast FY 2004-2014

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2005-2015

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2006-2016

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2007-2017

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2008-2018

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2009-2019

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2010-2020

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2011-2021

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Development of EDMI Calibration Baseline, HR-241, 1984

Electronic distance measuring instruments (EDMI) are used by surveyors in routine length measurements. The constant and scale factors of the instrument tend to change due to usage, transportation, and aging of crystals. Calibration baselines are established to enable surveyors to check the instruments and determine any changes in the values of constant and scale factors. The National Geodetic Survey (NGS) has developed guidelines for establishing these baselines. In 1981 an EDMI baseline at ISU was established according to NGS guidelines. In October 1982, the NGS measured the distances between monuments. Computer programs for reducing observed distances were developed. Mathematical model and computer programs for determining constant and scale factors were developed. A method was developed to detect any movements of the monuments. Periodic measurements of the baseline were made. No significant movement of the monuments was detected.

Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation

High-throughput prioritization of cancer-causing mutations (drivers) is a key challenge of cancer genome projects, due to the number of somatic variants detected in tumors. One important step in this task is to assess the functional impact of tumor somatic mutations. A number of computational methods have been employed for that purpose, although most were originally developed to distinguish disease-related nonsynonymous single nucleotide variants (nsSNVs) from polymorphisms. Our new method, transformed Functional Impact score for Cancer (transFIC), improves the assessment of the functional impact of tumor nsSNVs by taking into account the baseline tolerance of genes to functional variants.

Out-of-sample forecast tests robust to the choice of window size

This paper proposes new methodologies for evaluating out-of-sample forecastingperformance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide rangeof window sizes. We show that the tests proposed in the literature may lack the powerto detect predictive ability and might be subject to data snooping across differentwindow sizes if used repeatedly. An empirical application shows the usefulness of themethodologies for evaluating exchange rate models' forecasting ability.

Tree edit distance as a baseline approach for paraphrase representation

Finding an adequate paraphrase representation formalism is a challenging issue in Natural Language Processing. In this paper, we analyse the performance of Tree Edit Distance as a paraphrase representation baseline. Our experiments using Edit Distance Textual Entailment Suite show that, as Tree Edit Distance consists of a purely syntactic approach, paraphrase alternations not based on structural reorganizations do not find an adequate representation. They also show that there is much scope for better modelling of the way trees are aligned.

Asset Management Program Enhancement Plan: Baseline Assessment Phases I and II, 2015

This project resulted in the development of a framework for making asset management decisions on low-volume bridges. The research focused on low-volume bridges located in the agricultural counties of Iowa because recent research has shown that these counties have the greatest percentage of structurally deficient bridges in the nation. Many of the same counties also have the highest crop yields in the state, creating a situation where detours caused by deficient bridges on farm-to-market roads increase the cost to transport the crops. Thus, the research proposed the use of social return on investment (SROI), a tool used by international institutions such as the World Bank, as an asset management metric to gauge to the socioeconomic impact of structurally deficient bridges on the state in an effort to provide quantified justification to fund improvements on low-volume assets such as these rural bridges. The study found that combining SROI with current asset management metrics like average daily traffic (ADT) made it possible to prioritize the bridges in such a way that the limited resources available are allocated in a manner that promotes a more equitable distribution and that directly benefits the user, in this case Iowa farmers. The result is a system that more closely aligns itself with the spirit of MAP-21, in that infrastructure investments are used to facilitate economic growth for Iowa’s agricultural economy.

Analysis and Forecast of Housing Needs in Iowa Technical Report, January 22, 2013

The research and analysis summarized in this report prepared by Gruen Gruen + Associates (“GG+A”) provides an information base about population, household, housing, and employment conditions and trends affecting the current and future housing needs of Iowans. It also provides a synthesis of how the housing needs of Iowans have changed over the past decade and how needs are likely to continue to change over the present decade (2010-2020), given forecast employment and population growth in Iowa.