One-year prevalence of low back pain in two Swiss regions: estimates from the population participating in the 1992-1993 MONICA project.

STUDY DESIGN: A cross-sectional survey was performed. OBJECTIVE: To estimate the extent of low back pain as a public health problem. SUMMARY OF BACKGROUND DATA: Health surveys converge on very high estimates of low back pain in general populations, but few studies have included severity criteria in their definition and conclusions. Because it is unlikely that interventions will influence the prevalence of minimal and infrequent symptoms, greater attention should be paid to characteristics of low back pain that indicate some impact on the life of survey respondents. METHODS: Two regions participated in the MONICA (MONitoring of trends and determinants in CArdiovascular disease) project in Switzerland. Participants randomly selected from the general population completed a standard self-administered questionnaire on cardiovascular risk factors. A special section on low back pain was added in the third (1992-1993) MONICA survey and completed by 3227 participants. RESULTS: A regional difference found in the 12-month prevalence rate disappeared with the inclusion of severity criteria. Low back pain over more than seven cumulated days was reported among men by 20.2% (age range, 25-34 years) to 28.5% (age range, 65-74 years), respectively, among women by 31.1% to 38.5%. Similar rates of reduction in activity (professional, housekeeping, and leisure time) and medical consultation (conventional and nonconventional) motivated by low back pain characterized the two participating regions. The cumulative duration of pain was related to all the indicators showing the impact of low back pain on everyday life. CONCLUSIONS: Determining the cumulative duration of low back pain over the preceding year is a straightforward task, and a cutoff at 1 week seems appropriate for distinguishing between low- and high-impact low back pain.

Applying machine learning methods to avalanche forecasting

Avalanche forecasting is a complex process involving the assimilation of multiple data sources to make predictions over varying spatial and temporal resolutions. Numerically assisted forecasting often uses nearest neighbour methods (NN), which are known to have limitations when dealing with high dimensional data. We apply Support Vector Machines to a dataset from Lochaber, Scotland to assess their applicability in avalanche forecasting. Support Vector Machines (SVMs) belong to a family of theoretically based techniques from machine learning and are designed to deal with high dimensional data. Initial experiments showed that SVMs gave results which were comparable with NN for categorical and probabilistic forecasts. Experiments utilising the ability of SVMs to deal with high dimensionality in producing a spatial forecast show promise, but require further work.

The Iowa State Capitol Grounds 1913 Extension and Reconstruction Project, October 2012

The Capitol grounds have been evolving through planned and unplanned actions for more than 150 years. The 1857 Constitutio established Des Moines as the capital. The commissioners appointed to choose a site decided on land donated by Wilson Alexander Scott and Harrison Lyon. Located on the east side of the Des Moines River, on a gently rising hill, the site for the Iowa State Capitol began with fewer than 10 acres. The Old Brick Capitol was built in the center of that 10-acre plot, and the area to the north was used as a public park until work began on the present day Capitol. In 1884, the two-year process of moving from the Old Brick Capitol to the new Capitol began. The state commissioned John Weidenman to design the first formal decoration of the grounds. Weidenman’s plans for the west approach to the Capitol included planting statues, and walkways. The State held some additional land but not necessarily land adjacent to the Capitol. In 1909, legislation was passed, and in 1913, the Thirty-Fifth General Assembly enacted controversial legislation to acquire additional land. A commission was formed to locate a purposed monument honoring the long-serving U.S. Senator William B. Allison. E.L. Masqueray was hired as the architect expert focusing on the selection of a proper site for the proposed Allison Memorial. Masqueray’s plan detailed the placement of buildings and potential monuments. Growth of the Capitol Complex, as known today, began.

Pharmacy Pilot Project Showing Benefits, Data Download, January 2014

In 2013, released offenders with a mental illness were made eligible to obtain a free 60-day supply of behavioral health medications in addition to the 30-day supply already provided by the Department of Corrections. The Iowa Medication Voucher Program provided the funding, which allowed the DOC Central Pharmacy to dispense the approved medications to participating pharmacies in 95 counties.

Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data.

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

Underseal Evaluation Project: Poweshiek County I-80 Near Milepost 189.5, Eastbound Roadway, MLR-85-10, 1985

The purpose of this project was to determine the optimal hole pattern needed for undersealing work, and also to determine if it is feasible to underseal a roadway with existing longitudinal subdrains without plugging the subdrain system. At the test site the hole pattern had little effect on the grout distribution. It was found that the hole pattern, to be effective, must locate existing voids and that holes must extend at least 2 in. (5 cm) below the underside of the pavement. It appeared that pavements can be undersealed without significant damage to the existing subdrains, but special care is needed to assure that excess grout is not injected into the drainage system. Recommendations are made concerning the hole pattern, grout efflux time, and procedures for minimizing the risk of plugging the subdrains with grout.

Project Newsletter Iowa Public Health Tracking, December 2013

The IDPH Public Health Tracking Program is an excellent way to collect data related to various indicators for Iowans, but those looking for national statistics or data from other states may want to check out the Health Indicators Warehouse (healthindicators.gov). Run and maintained by the CDC’s National Center for Health Statistics, this site is a centralized source for national, state, and county data for a wide variety of indicators. The data is available to the public, and can be accessed either through the tables and charts directly on the website, or indicators can be downloaded to use in a spreadsheet. Once on the site, users are able to search for their desired data either by topic or geographic region. Filters can then be applied to the chosen field to narrow down the user’s search and obtain the preferred statistics. In addition, users are also able to search for indicators derived from state and federal health indicator initiatives: County Health Rankings, Community Health Status Indicators, Healthy People 2020, and CMS Community Indicators. The warehouse provides an overview of each indicator after the user has made their selection. This overview includes information on how the data was calculated and what characteristics are being represented. For example, percent of binge drinking adults is prefaced in the overview that data was based on the question: “Considering all types of alcoholic beverages, how many times during the past 30 days did you have [5 for men, 4 for women] or more drinks on an occasion?" Data is viewable either in the basic table format, chart format, or for some indicators it is possible to view it in terms of a national map. The Health Indicators Warehouse updates indicators as data becomes available, but the collection of years varies amongst the indicators. Nonetheless, this site is a useful resource to anyone looking for comparative indicators throughout the nation or is interested in one of the hundreds of indicators housed by the site. For more information or to check out what the warehouse has to offer visit: http://healthindicators.gov/

Project Newsletter Iowa Public Health Tracking, January 2014

The IDPH Public Health Tracking Program is an excellent way to collect data related to various indicators for Iowans, but those looking for national statistics or data from other states may want to check out the Health Indicators Warehouse (healthindicators.gov). Run and maintained by the CDC’s National Center for Health Statistics, this site is a centralized source for national, state, and county data for a wide variety of indicators. The data is available to the public, and can be accessed either through the tables and charts directly on the website, or indicators can be downloaded to use in a spreadsheet. Once on the site, users are able to search for their desired data either by topic or geographic region. Filters can then be applied to the chosen field to narrow down the user’s search and obtain the preferred statistics. In addition, users are also able to search for indicators derived from state and federal health indicator initiatives: County Health Rankings, Community Health Status Indicators, Healthy People 2020, and CMS Community Indicators. The warehouse provides an overview of each indicator after the user has made their selection. This overview includes information on how the data was calculated and what characteristics are being represented. For example, percent of binge drinking adults is prefaced in the overview that data was based on the question: “Considering all types of alcoholic beverages, how many times during the past 30 days did you have [5 for men, 4 for women] or more drinks on an occasion?" Data is viewable either in the basic table format, chart format, or for some indicators it is possible to view it in terms of a national map. The Health Indicators Warehouse updates indicators as data becomes available, but the collection of years varies amongst the indicators. Nonetheless, this site is a useful resource to anyone looking for comparative indicators throughout the nation or is interested in one of the hundreds of indicators housed by the site. For more information or to check out what the warehouse has to offer visit: http://healthindicators.gov/

Field Evaluation of Compaction Monitoring Technology: Phase II Volumes 1 and 2, TR-495, 2006

This report documents an extensive field program carried out to identify the relationships between soil engineering properties, as measured by various in situ devices, and the results of machine compaction monitoring using prototype compaction monitoring technology developed by Caterpillar Inc. Primary research tasks for this study include the following: (1) experimental testing and statistical analyses to evaluate machine power in terms of the engineering properties of the compacted soil (e.g., density, strength, stiffness) and (2) recommendations for using the compaction monitoring technology in practice. The compaction monitoring technology includes sensors that monitor the power consumption used to move the compaction machine, an on-board computer and display screen, and a GPS system to map the spatial location of the machine. In situ soil density, strength, and stiffness data characterized the soil at various stages of compaction. For each test strip or test area, in situ soil properties were compared directly to machine power values to establish statistical relationships. Statistical models were developed to predict soil density, strength, and stiffness from the machine power values. Field data for multiple test strips were evaluated. The R2 correlation coefficient was generally used to assess the quality of the regressions. Strong correlations were observed between averaged machine power and field measurement data. The relationships are based on the compaction model derived from laboratory data. Correlation coefficients (R2) were consistently higher for thicker lifts than for thin lifts, indicating that the depth influencing machine power response exceeds the representative lift thickness encountered under field conditions. Caterpillar Inc. compaction monitoring technology also identified localized areas of an earthwork project with weak or poorly compacted soil. The soil properties at these locations were verified using in situ test devices. This report also documents the steps required to implement the compaction monitoring technology evaluated.

Project Newsletter Iowa Public Health Tracking, February 2014

The IDPH Public Health Tracking Program is an excellent way to collect data related to various indicators for Iowans, but those looking for national statistics or data from other states may want to check out the Health Indicators Warehouse (healthindicators.gov). Run and maintained by the CDC’s National Center for Health Statistics, this site is a centralized source for national, state, and county data for a wide variety of indicators. The data is available to the public, and can be accessed either through the tables and charts directly on the website, or indicators can be downloaded to use in a spreadsheet. Once on the site, users are able to search for their desired data either by topic or geographic region. Filters can then be applied to the chosen field to narrow down the user’s search and obtain the preferred statistics. In addition, users are also able to search for indicators derived from state and federal health indicator initiatives: County Health Rankings, Community Health Status Indicators, Healthy People 2020, and CMS Community Indicators. The warehouse provides an overview of each indicator after the user has made their selection. This overview includes information on how the data was calculated and what characteristics are being represented. For example, percent of binge drinking adults is prefaced in the overview that data was based on the question: “Considering all types of alcoholic beverages, how many times during the past 30 days did you have [5 for men, 4 for women] or more drinks on an occasion?" Data is viewable either in the basic table format, chart format, or for some indicators it is possible to view it in terms of a national map. The Health Indicators Warehouse updates indicators as data becomes available, but the collection of years varies amongst the indicators. Nonetheless, this site is a useful resource to anyone looking for comparative indicators throughout the nation or is interested in one of the hundreds of indicators housed by the site. For more information or to check out what the warehouse has to offer visit: http://healthindicators.gov/

Iowa Power Fund Board Project Report Update, November 12, 2008

ISU’s proposed research will (1) develop methods for designing clean and efficient burners for low‐Btu producer gas and medium‐Btu syngas, (2) develop catalysts and flow reactors to produce ethanol from medium‐Btu synthesis gas, and (3) upgrade the BECON gasifier system to enable medium‐Btu syngas production and greatly enhanced capabilities for detailed gas analysis needed by both (1) and (2). This project addresses core development needs to enable grain ethanol industry reduce its natural gas demand and ultimately transition to cellulosic ethanol production.

Feasibility of Using Automated Distress Data in the County Need Study, TR-418, 1998

The purpose of this project was to determine the feasibility of using pavement condition data collected for the Iowa Pavement Management Program (IPMP) as input to the Iowa Quadrennial Need Study. The need study, conducted by the Iowa Department of Transportation (Iowa DOT) every four years, currently uses manually collected highway infrastructure condition data (roughness, rutting, cracking, etc.). Because of the Iowa DOT's 10-year data collection cycles, condition data for a given highway segment may be up to 10 years old. In some cases, the need study process has resulted in wide fluctuations in funding allocated to individual Iowa counties from one study to the next. This volatility in funding levels makes it difficult for county engineers to plan and program road maintenance and improvements. One possible remedy is to input more current and less subjective infrastructure condition data. The IPMP was initially developed to satisfy the Intermodal Surface Transportation Efficiency Act (ISTEA) requirement that federal-aid-eligible highways be managed through a pavement management system. Currently all metropolitan planning organizations (MPOs) in Iowa and 15 of Iowa's 18 RPAs participate in the IPMP. The core of this program is a statewide data base of pavement condition and construction history information. The pavement data are collected by machine in two-year cycles. Using pilot areas, researchers examined the implications of using the automated data collected for the IPMP as input to the need study computer program, HWYNEEDS. The results show that using the IPMP automated data in HWYNEEDS is feasible and beneficial, resulting in less volatility in the level of total need between successive quadrennial need studies. In other words, the more current the data, the smaller the shift in total need.