2007 Annual Report Capitol Planning Commission, January 2008

The Capitol Planning Commission is authorized under Chapter 8A.371—378 of the Code of Iowa. “It shall be the duty of the commission to advise upon the location of statues, fountains and monuments and the placing of any additional buildings on the capitol grounds, the type of architecture and the type of construction of any new buildings to be erected on the state capitol grounds as now encompassed or as subsequently enlarged, and repairs and restoration thereof, and it shall be the duty of the officers, commissions, and councils charged by law with the duty of determining such questions to call upon the commission for such advice. “The commission shall, in cooperation with the director of the department of administrative services, develop and implement within the limits of its appropriation, a five-year modernization program for the capitol complex. “The commission shall annually report to the general assembly its recommendations relating to its duties under this section. The report shall be submitted to the chief clerk of the house and the secretary of the senate during the month of January.” —Code of Iowa, Chapter 8A.373

2010 Annual Report Capitol Planning Commission, January 2011

The Capitol Planning Commission is authorized under Chapter 8A.371—378 of the Code of Iowa. “It shall be the duty of the commission to advise upon the location of statues, fountains and monuments and the placing of any additional buildings on the capitol grounds, the type of architecture and the type of construction of any new buildings to be erected on the state capitol grounds as now encompassed or as subsequently enlarged, and repairs and restoration thereof, and it shall be the duty of the officers, commissions, and councils charged by law with the duty of determining such questions to call upon the commission for such advice. “The commission shall, in cooperation with the director of the department of administrative services, develop and implement within the limits of its appropriation, a five-year modernization program for the capitol complex. “The commission shall annually report to the general assembly its recommendations relating to its duties under this section. The report shall be submitted to the chief clerk of the house and the secretary of the senate during the month of January.” —Code of Iowa, Chapter 8A.373

Sustainability of Wood Productivity of Pinus TaedaBased on Nutrient Export and Stocks in the Biomass and in the Soil

ABSTRACT The impact of intensive management practices on the sustainability of forest production depends on maintenance of soil fertility. The contribution of forest residues and nutrient cycling in this process is critical. A 16-year-old stand of Pinus taeda in a Cambissolo Húmico Alumínico léptico (Humic Endo-lithic Dystrudept) in the south of Brazil was studied. A total of 10 trees were sampled distributed in five diameter classes according to diameter at breast height. The biomass of the needles, twigs, bark, wood, and roots was measured for each tree. In addition to plant biomass, accumulated plant litter was sampled, and soil samples were taken at three increments based on sampling depth: 0.00-0.20, 0.20-0.40, 0.40-0.60, 0.60-1.00, 1.00-1.40, 1.40-1.80, and 1.80-1.90 m. The quantity and concentration of nutrients, as well as mineralogical characteristics, were determined for each soil sample. Three scenarios of harvesting intensities were simulated: wood removal (A), wood and bark removal (B), and wood + bark + canopy removal (C). The sum of all biomass components was 313 Mg ha-1.The stocks of nutrients in the trees decreased in the order N>Ca>K>S>Mg>P. The mineralogy of the Cambissolo Húmico Alumínico léptico showed the predominance of quartz sand and small traces of vermiculite in the silt fraction. Clay is the main fraction that contributes to soil weathering, due to the transformation of illite-vermiculite, releasing K. The depletion of nutrients from the soil biomass was in the order: P>S>N>K>Mg>Ca. Phosphorus and S were the most limiting in scenario A due to their low stock in the soil. In scenario B, the number of forest rotations was limited by N, K, and S. Scenario C showed the greatest reduction in productivity, allowing only two rotations before P limitation. It is therefore apparent that there may be a difference of up to 30 years in the capacity of the soil to support a scenario such as A, with a low nutrient removal, compared to scenario C, with a high nutrient removal. Hence, the effect of different harvesting intensities on nutrient availability may jeopardize the sustainability of P. taeda in the short-term.

A systematic review of longitudinal population-based studies on the predictors of smoking cessation in adolescent and young adult smokers.

OBJECTIVE: To describe the determinants of self-initiated smoking cessation of duration of at least 6 months as identified in longitudinal population-based studies of adolescent and young adult smokers. METHODS: A systematic search of the PubMed and EMBASE databases using smoking, tobacco, cessation, quit and stop as keywords was performed. Limits included articles related to humans, in English, published between January 1984 and August 2010, and study population aged 10-29 years. A total of 4502 titles and 871 abstracts were reviewed independently by 2 and 3 reviewers, respectively. Nine articles were retained for data abstraction. Data on study location, timeframe, duration of follow-up, number of data collection points, sample size, age/grade of participants, number of quitters, smoking status at baseline, definition of cessation, covariates and analytic method were abstracted from each article. The number of studies that reported a statistically significant association between each determinant investigated and cessation were tabulated, from among all studies that assessed the determinant. RESULTS: Despite heterogeneity in methods across studies, five factors robustly predicted quitting across studies in which the factor was investigated: not having friends who smoke, not having intentions to smoke in the future, resisting peer pressure to smoke, being older at first use of cigarette and having negative beliefs about smoking. CONCLUSIONS: The literature on longitudinal predictors of cessation in adolescent and young adult smokers is not well developed. Cessation interventions for this population will remain less than optimally effective until there is a solid evidence base on which to develop interventions.

Fas (CD95/APO-1) limits the expansion of T lymphocytes in an environment of limited T-cell antigen receptor/MHC contacts.

Fas-deficient mice (Fas(lpr/lpr)) and humans have profoundly dysregulated T lymphocyte homeostasis, which manifests as an accumulation of CD4(+) and CD8(+) T cells as well as an unusual population of CD4(-)CD8(-)TCRαβ(+) T cells. To date, no unifying model has explained both the increased T-cell numbers and the origin of the CD4(-)CD8(-)TCRαβ(+) T cells. As Fas(lpr/lpr) mice raised in a germ-free environment still manifest lymphadenopathy, we considered that this process is primarily driven by recurrent low-avidity TCR signaling in response to self-peptide/MHC as occurs during homeostatic proliferation. In these studies, we developed two independent systems to decrease the number of self-peptide/MHC contacts. First, expression of MHC class I was reduced in OT-I TCR transgenic mice. Although OT-I Fas(lpr/lpr) mice did not develop lymphadenopathy characteristic of Fas(lpr/lpr) mice, in the absence of MHC class I, OT-I Fas(lpr/lpr) T cells accumulated as both CD8(+) and CD4(-)CD8(-) T cells. In the second system, re-expression of β(2)m limited to thymic cortical epithelial cells of Fas(lpr/lpr) β(2)m-deficient mice yielded a model in which polyclonal CD8(+) thymocytes entered a peripheral environment devoid of MHC class I. These mice accumulated significantly greater numbers of CD4(-)CD8(-)TCRαβ(+) T cells than conventional Fas(lpr/lpr) mice. Thus, Fas shapes the peripheral T-cell repertoire by regulating the survival of a subset of T cells proliferating in response to limited self-peptide/MHC contacts.

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.

Commissioner’s Planning Guidance, 2013

As technology evolves, vital resources shift, and the state’s population diversifies, Public Safety will have a unique opportunity to show our integrity, values, and worth to the citizens of Iowa. To take advantage of this unique moment in history, and will remain committed to, proactive and on-going strategic mapping. This strategic work will always be guided by Public Safety’s mission and core values, as well as by our responsibility to support local Police Departments and Sheriff’s Offices.

Missouri Work Zone Capacity: Results of Field Data Analysis, TPF-5(081), 2011

This report presents the results of work zone field data analyzed on interstate highways in Missouri to determine the mean breakdown and queue-discharge flow rates as measures of capacity. Several days of traffic data collected at a work zone near Pacific, Missouri with a speed limit of 50 mph were analyzed in both the eastbound and westbound directions. As a result, a total of eleven breakdown events were identified using average speed profiles. The traffic flows prior to and after the onset of congestion were studied. Breakdown flow rates ranged between 1194 to 1404 vphpl, with an average of 1295 vphpl, and a mean queue discharge rate of 1072 vphpl was determined. Mean queue discharge, as used by the Highway Capacity Manual 2000 (HCM), in terms of pcphpl was found to be 1199, well below the HCM’s average capacity of 1600 pcphpl. This reduced capacity found at the site is attributable mainly to narrower lane width and higher percentage of heavy vehicles, around 25%, in the traffic stream. The difference found between mean breakdown flow (1295 vphpl) and queue-discharge flow (1072 vphpl) has been observed widely, and is due to reduced traffic flow once traffic breaks down and queues start to form. The Missouri DOT currently uses a spreadsheet for work zone planning applications that assumes the same values of breakdown and mean queue discharge flow rates. This study proposes that breakdown flow rates should be used to forecast the onset of congestion, whereas mean queue discharge flow rates should be used to estimate delays under congested conditions. Hence, it is recommended that the spreadsheet be refined accordingly.