A-1 - Monthly Public Assistance Statistical Report Family Investment Program, November 2015

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 - Monthly Public Assistance Statistical Report Family Investment Program, December 2015

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 - Monthly Public Assistance Statistical Report Family Investment Program, January 2016

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

Statistical significance of quantitative PCR.

BACKGROUND: PCR has the potential to detect and precisely quantify specific DNA sequences, but it is not yet often used as a fully quantitative method. A number of data collection and processing strategies have been described for the implementation of quantitative PCR. However, they can be experimentally cumbersome, their relative performances have not been evaluated systematically, and they often remain poorly validated statistically and/or experimentally. In this study, we evaluated the performance of known methods, and compared them with newly developed data processing strategies in terms of resolution, precision and robustness. RESULTS: Our results indicate that simple methods that do not rely on the estimation of the efficiency of the PCR amplification may provide reproducible and sensitive data, but that they do not quantify DNA with precision. Other evaluated methods based on sigmoidal or exponential curve fitting were generally of both poor resolution and precision. A statistical analysis of the parameters that influence efficiency indicated that it depends mostly on the selected amplicon and to a lesser extent on the particular biological sample analyzed. Thus, we devised various strategies based on individual or averaged efficiency values, which were used to assess the regulated expression of several genes in response to a growth factor. CONCLUSION: Overall, qPCR data analysis methods differ significantly in their performance, and this analysis identifies methods that provide DNA quantification estimates of high precision, robustness and reliability. These methods allow reliable estimations of relative expression ratio of two-fold or higher, and our analysis provides an estimation of the number of biological samples that have to be analyzed to achieve a given precision.

A-1 - Monthly Public Assistance Statistical Report Family Investment Program, February 2016

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 - Monthly Public Assistance Statistical Report Family Investment Program, March 2016

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

Statistical Summaries of Selected Iowa Streamflow Data Through September 2013, TR-669

This report is the final product of a two-year study that began October 1, 2013. In addition to the funding provided for this study by the Iowa Highway Research Board and the Iowa Department of Transportation (TR-669), the project was also funded by the U.S. Army Corps of Engineers and the U.S. Geological Survey. The report was published as an online report on January 4, 2016. The report is available online at http://dx.doi.org/10.3133/ofr20151214 . The main body of the report provides a description of the statistics presented for the streamgages and an explanation of the streamgage summaries, also included is a discussion of the USGS streamgage network in Iowa. Individual streamgage summaries are available as links listed in table 1, or all 184 streamgage summaries are available in a zipped file named “Streamgage Summaries.”

Embankment Quality and Assessment of Moisture Control Implementation, TR-677, 2016

A specification for contractor moisture quality control (QC) in roadway embankment construction has been in use for approximately 10 years in Iowa on about 190 projects. The use of this QC specification and the development of the soils certification program for the Iowa Department of Transportation (DOT) originated from Iowa Highway Research Board (IHRB) embankment quality research projects. Since this research, the Iowa DOT has applied compaction with moisture control on most embankment work under pavements. This study set out to independently evaluate the actual quality of compaction using the current specifications. Results show that Proctor tests conducted by Iowa State University (ISU) using representative material obtained from each test section where field testing was conducted had optimum moisture contents and maximum dry densities that are different from what was selected by the Iowa DOT for QC/quality assurance (QA) testing. Comparisons between the measured and selected values showed a standard error of 2.9 lb/ft3 for maximum dry density and 2.1% for optimum moisture content. The difference in optimum moisture content was as high as 4% and the difference in maximum dry density was as high as 6.5 lb/ft3 . The difference at most test locations, however, were within the allowable variation suggested in AASHTO T 99 for test results between different laboratories. The ISU testing results showed higher rates of data outside of the target limits specified based on the available contractor QC data for cohesive materials. Also, during construction observations, wet fill materials were often observed. Several test points indicated that materials were placed and accepted at wet of the target moisture contents. The statistical analysis results indicate that the results obtained from this study showed improvements over results from previous embankment quality research projects (TR-401 Phases I through III and TR-492) in terms of the percentage of data that fell within the specification limits. Although there was evidence of improvement, QC/QA results are not consistently meeting the target limits/values. Recommendations are provided in this report for Iowa DOT consideration with three proposed options for improvements to the current specifications. Option 1 provides enhancements to current specifications in terms of material-dependent control limits, training, sampling, and process control. Option 2 addresses development of alternative specifications that incorporate dynamic cone penetrometer or light weight deflectometer testing into QC/QA. Option 3 addresses incorporating calibrated intelligent compaction measurements into QC/QA.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

A-1 - Monthly Public Assistance Statistical Report Family Investment Program, April 2016

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

Statistical methods for river runoff prediction

Methods used to analyze one type of nonstationary stochastic processes?the periodically correlated process?are considered. Two methods of one-step-forward prediction of periodically correlated time series are examined. One-step-forward predictions made in accordance with an autoregression model and a model of an artificial neural network with one latent neuron layer and with an adaptation mechanism of network parameters in a moving time window were compared in terms of efficiency. The comparison showed that, in the case of prediction for one time step for time series of mean monthly water discharge, the simpler autoregression model is more efficient.

Evidence of systematic and proportional error in a widely used glucose oxidase analyser: Impact for clinical research?

Real time glycemia is a cornerstone for metabolic research, particularly when performing oral glucose tolerance tests (OGTT) or glucose clamps. From 1965 to 2009, the gold standard device for real time plasma glucose assessment was the Beckman glucose analyzer 2 (Beckman Instruments, Fullerton, CA), which technology couples glucose oxidase enzymatic assay with oxygen sensors. Since its discontinuation in 2009, today's researchers are left with few choices that utilize glucose oxidase technology. The first one is the YSI 2300 (Yellow Springs Instruments Corp., Yellow Springs, OH), known to be as accurate as the Beckman(1). The YSI has been used extensively for clinical research studies and is used to validate other glucose monitoring devices(2). The major drawback of the YSI is that it is relatively slow and requires high maintenance. The Analox GM9 (Analox instruments, London), more recent and faster, is increasingly used in clinical research(3) as well as in basic sciences(4) (e.g. 23 papers in Diabetes or 21 in Diabetologia). This article is protected by copyright. All rights reserved.

JPEG standard uniform quantization error modeling with applications to sequential and progressive operation modes

In this paper we propose a method for computing JPEG quantization matrices for a given mean square error or PSNR. Then, we employ our method to compute JPEG standard progressive operation mode definition scripts using a quantization approach. Therefore, it is no longer necessary to use a trial and error procedure to obtain a desired PSNR and/or definition script, reducing cost. Firstly, we establish a relationship between a Laplacian source and its uniform quantization error. We apply this model to the coefficients obtained in the discrete cosine transform stage of the JPEG standard. Then, an image may be compressed using the JPEG standard under a global MSE (or PSNR) constraint and a set of local constraints determined by the JPEG standard and visual criteria. Secondly, we study the JPEG standard progressive operation mode from a quantization based approach. A relationship between the measured image quality at a given stage of the coding process and a quantization matrix is found. Thus, the definition script construction problem can be reduced to a quantization problem. Simulations show that our method generates better quantization matrices than the classical method based on scaling the JPEG default quantization matrix. The estimation of PSNR has usually an error smaller than 1 dB. This figure decreases for high PSNR values. Definition scripts may be generated avoiding an excessive number of stages and removing small stages that do not contribute during the decoding process with a noticeable image quality improvement.

Bootstrapping a statistical speech translator from a rule-based one

We describe a series of experiments in which we start with English to French and English to Japanese versions of an Open Source rule-based speech translation system for a medical domain, and bootstrap correspondign statistical systems. Comparative evaluation reveals that the rule-based systems are still significantly better than the statistical ones, despite the fact that considerable effort has been invested in tuning both the recognition and translation components; also, a hybrid system only marginally improved recall at the cost of a los in precision. The result suggests that rule-based architectures may still be preferable to statistical ones for safety-critical speech translation tasks.

Oops! Another medication error : a literature review of contributing factors and methods to prevent medication errors

The purpose of this bachelor's thesis was to chart scientific research articles to present contributing factors to medication errors done by nurses in a hospital setting, and introduce methods to prevent medication errors. Additionally, international and Finnish research was combined and findings were reflected in relation to the Finnish health care system. Literature review was conducted out of 23 scientific articles. Data was searched systematically from CINAHL, MEDIC and MEDLINE databases, and also manually. Literature was analysed and the findings combined using inductive content analysis. Findings revealed that both organisational and individual factors contributed to medication errors. High workload, communication breakdowns, unsuitable working environment, distractions and interruptions, and similar medication products were identified as organisational factors. Individual factors included nurses' inability to follow protocol, inadequate knowledge of medications and personal qualities of the nurse. Developing and improving the physical environment, error reporting, and medication management protocols were emphasised as methods to prevent medication errors. Investing to the staff's competence and well-being was also identified as a prevention method. The number of Finnish articles was small, and therefore the applicability of the findings to Finland is difficult to assess. However, the findings seem to fit to the Finnish health care system relatively well. Further research is needed to identify those factors that contribute to medication errors in Finland. This is a necessity for the development of methods to prevent medication errors that fit in to the Finnish health care system.