Development of Abutment Design Standards for Local Bridge Designs, Volume 3 of 3, Verification of Design Methodology, August 2004

Several superstructure design methodologies have been developed for low volume road bridges by the Iowa State University Bridge Engineering Center. However, to date no standard abutment designs have been developed. Thus, there was a need to establish an easy to use design methodology in addition to generating generic abutment standards and other design aids for the more common substructure systems used in Iowa. The final report for this project consists of three volumes. The first volume summarizes the research completed in this project. A survey of the Iowa County Engineers was conducted from which it was determined that while most counties use similar types of abutments, only 17 percent use some type of standard abutment designs or plans. A literature review revealed several possible alternative abutment systems for future use on low volume road bridges in addition to two separate substructure lateral load analysis methods. These consisted of a linear and a non-linear method. The linear analysis method was used for this project due to its relative simplicity and the relative accuracy of the maximum pile moment when compared to values obtained from the more complex non-linear analysis method. The resulting design methodology was developed for single span stub abutments supported on steel or timber piles with a bridge span length ranging from 20 to 90 ft and roadway widths of 24 and 30 ft. However, other roadway widths can be designed using the foundation design template provided. The backwall height is limited to a range of 6 to 12 ft, and the soil type is classified as cohesive or cohesionless. The design methodology was developed using the guidelines specified by the American Association of State Highway Transportation Officials Standard Specifications, the Iowa Department of Transportation Bridge Design Manual, and the National Design Specifications for Wood Construction. The second volume introduces and outlines the use of the various design aids developed for this project. Charts for determining dead and live gravity loads based on the roadway width, span length, and superstructure type are provided. A foundation design template was developed in which the engineer can check a substructure design by inputting basic bridge site information. Tables published by the Iowa Department of Transportation that provide values for estimating pile friction and end bearing for different combinations of soils and pile types are also included. Generic standard abutment plans were developed for which the engineer can provide necessary bridge site information in the spaces provided. These tools enable engineers to design and detail county bridge substructures more efficiently. The third volume (this volume) provides two sets of calculations that demonstrate the application of the substructure design methodology developed in this project. These calculations also verify the accuracy of the foundation design template. The printouts from the foundation design template are provided at the end of each example. Also several tables provide various foundation details for a pre-cast double tee superstructure with different combinations of soil type, backwall height, and pile type.

Development of Abutment Design Standards for Local Bridge Designs, Volume 2 of 3, Design Manual, August 2004

Several superstructure design methodologies have been developed for low volume road bridges by the Iowa State University Bridge Engineering Center. However, to date no standard abutment designs have been developed. Thus, there was a need to establish an easy to use design methodology in addition to generating generic abutment standards and other design aids for the more common substructure systems used in Iowa. The final report for this project consists of three volumes. The first volume summarizes the research completed in this project. A survey of the Iowa County Engineers was conducted from which it was determined that while most counties use similar types of abutments, only 17 percent use some type of standard abutment designs or plans. A literature review revealed several possible alternative abutment systems for future use on low volume road bridges in addition to two separate substructure lateral load analysis methods. These consisted of a linear and a non-linear method. The linear analysis method was used for this project due to its relative simplicity and the relative accuracy of the maximum pile moment when compared to values obtained from the more complex non-linear analysis method. The resulting design methodology was developed for single span stub abutments supported on steel or timber piles with a bridge span length ranging from 20 to 90 ft and roadway widths of 24 and 30 ft. However, other roadway widths can be designed using the foundation design template provided. The backwall height is limited to a range of 6 to 12 ft, and the soil type is classified as cohesive or cohesionless. The design methodology was developed using the guidelines specified by the American Association of State Highway Transportation Officials Standard Specifications, the Iowa Department of Transportation Bridge Design Manual, and the National Design Specifications for Wood Construction. The second volume (this volume) introduces and outlines the use of the various design aids developed for this project. Charts for determining dead and live gravity loads based on the roadway width, span length, and superstructure type are provided. A foundation design template was developed in which the engineer can check a substructure design by inputting basic bridge site information. Tables published by the Iowa Department of Transportation that provide values for estimating pile friction and end bearing for different combinations of soils and pile types are also included. Generic standard abutment plans were developed for which the engineer can provide necessary bridge site information in the spaces provided. These tools enable engineers to design and detail county bridge substructures more efficiently. The third volume provides two sets of calculations that demonstrate the application of the substructure design methodology developed in this project. These calculations also verify the accuracy of the foundation design template. The printouts from the foundation design template are provided at the end of each example. Also several tables provide various foundation details for a pre-cast double tee superstructure with different combinations of soil type, backwall height, and pile type.

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

BME-based uncertainty assessment of the Chernobyl fallout

The vast territories that have been radioactively contaminated during the 1986 Chernobyl accident provide a substantial data set of radioactive monitoring data, which can be used for the verification and testing of the different spatial estimation (prediction) methods involved in risk assessment studies. Using the Chernobyl data set for such a purpose is motivated by its heterogeneous spatial structure (the data are characterized by large-scale correlations, short-scale variability, spotty features, etc.). The present work is concerned with the application of the Bayesian Maximum Entropy (BME) method to estimate the extent and the magnitude of the radioactive soil contamination by 137Cs due to the Chernobyl fallout. The powerful BME method allows rigorous incorporation of a wide variety of knowledge bases into the spatial estimation procedure leading to informative contamination maps. Exact measurements (?hard? data) are combined with secondary information on local uncertainties (treated as ?soft? data) to generate science-based uncertainty assessment of soil contamination estimates at unsampled locations. BME describes uncertainty in terms of the posterior probability distributions generated across space, whereas no assumption about the underlying distribution is made and non-linear estimators are automatically incorporated. Traditional estimation variances based on the assumption of an underlying Gaussian distribution (analogous, e.g., to the kriging variance) can be derived as a special case of the BME uncertainty analysis. The BME estimates obtained using hard and soft data are compared with the BME estimates obtained using only hard data. The comparison involves both the accuracy of the estimation maps using the exact data and the assessment of the associated uncertainty using repeated measurements. Furthermore, a comparison of the spatial estimation accuracy obtained by the two methods was carried out using a validation data set of hard data. Finally, a separate uncertainty analysis was conducted that evaluated the ability of the posterior probabilities to reproduce the distribution of the raw repeated measurements available in certain populated sites. The analysis provides an illustration of the improvement in mapping accuracy obtained by adding soft data to the existing hard data and, in general, demonstrates that the BME method performs well both in terms of estimation accuracy as well as in terms estimation error assessment, which are both useful features for the Chernobyl fallout study.

Evaluation of C-reactive protein, procalcitonin, tumor necrosis factor alpha, interleukin-6, and interleukin-8 as diagnostic parameters in sepsis-related fatalities.

The aims of this study were to investigate the usefulness of serum C-reactive protein, procalcitonin, tumor necrosis factor alpha, interleukin-6, and interleukin-8 as postmortem markers of sepsis and to compare C-reactive protein and procalcitonin values in serum, vitreous humor, and cerebrospinal fluid in a series of sepsis cases and control subjects, in order to determine whether these measurements may be employed for the postmortem diagnosis of sepsis. Two study groups were formed, a sepsis group (eight subjects coming from the intensive care unit of two university hospitals, with a clinical diagnosis of sepsis in vivo) and control group (ten autopsy cases admitted to two university medicolegal centers, deceased from natural and unnatural causes, without elements to presume an underlying sepsis as the cause of death). Serum C-reactive protein and procalcitonin concentrations were significantly different between sepsis cases and control cases, whereas serum tumor necrosis factor alpha, interleukin-6, and interleukin-8 values were not significantly different between the two groups, suggesting that measurement of interleukin-6, interleukin-8, and tumor necrosis factor alpha is non-optimal for postmortem discrimination of cases with sepsis. In the sepsis group, vitreous procalcitonin was detectable in seven out of eight cases. In the control group, vitreous procalcitonin was clearly detectable only in one case, which also showed an increase of all markers in serum and for which the cause of death was myocardial infarction associated with multi-organic failure. According to the results of this study, the determination of vitreous procalcitonin may be an alternative to the serum procalcitonin for the postmortem diagnosis of sepsis.

Estimating overidentified, nonrecursive, time-varying coefficients structural VARs

This paper provides a method to estimate time varying coefficients structuralVARs which are non-recursive and potentially overidentified. The procedureallows for linear and non-linear restrictions on the parameters, maintainsthe multi-move structure of standard algorithms and can be used toestimate structural models with different identification restrictions. We studythe transmission of monetary policy shocks and compare the results with thoseobtained with traditional methods.

Behavioral ecology of Heteragrion consors Hagen (Odonata, Megapodagrionidae): a shade-seek Atlantic forest damselfly

Behavioral ecology of Heteragrion consors Hagen (Odonata: Megapodagrionidae): a shade-seek Atlantic forest damselfly. The intensity of the inter and intra-sexual selection can affect male behavioral traits as territorial fidelity and aggressiveness allowing the existence of different strategies. However, its differential success could be affected by environmental - as the diel variation in temperature - and physiological constrains - as the variation in thermoregulatory abilities. In this context, we present a behavioral analysis of Heteragrion consors (Zygoptera, Megapodagrionidae) trying to characterize its mating system, diel activity pattern, temporal budget, territoriality and reproductive biology. These data were obtained based on field observations using the focal individual method and mark-recapture techniques in 120 m of a shaded Atlantic Forest stream in Brazil. The males of this species were territorial, varying in its local fidelity, while the females appear sporadically. Males were perched in the majority of the time, but were also observed in cleaning movements, longitudinal abdominal flexion, wing flexion and sperm transfer during perch. The males presented a perched thermoregulatory behavior related to an exothermic regulation. Foraging and agonistic interactions were rare, but dominate the other behavioral activities. Abdominal movements associated to long lasting copula pointed to the existence of sperm competition in this species. Males performed contact post-copulatory guarding of the females. These observations pointed to a non-resource mating system for this species.

Estimating the time since discharge of spent cartridges: a logical approach fro interpreting the evidence

Estimating the time since discharge of a spent cartridge or a firearm can be useful in criminal situa-tions involving firearms. The analysis of volatile gunshot residue remaining after shooting using solid-phase microextraction (SPME) followed by gas chromatography (GC) was proposed to meet this objective. However, current interpretative models suffer from several conceptual drawbacks which render them inadequate to assess the evidential value of a given measurement. This paper aims to fill this gap by proposing a logical approach based on the assessment of likelihood ratios. A probabilistic model was thus developed and applied to a hypothetical scenario where alternative hy-potheses about the discharge time of a spent cartridge found on a crime scene were forwarded. In order to estimate the parameters required to implement this solution, a non-linear regression model was proposed and applied to real published data. The proposed approach proved to be a valuable method for interpreting aging-related data.

Classification of urban multi-angular image sequences by aligning their manifolds

When dealing with multi-angular image sequences, problems of reflectance changes due either to illumination and acquisition geometry, or to interactions with the atmosphere, naturally arise. These phenomena interplay with the scene and lead to a modification of the measured radiance: for example, according to the angle of acquisition, tall objects may be seen from top or from the side and different light scatterings may affect the surfaces. This results in shifts in the acquired radiance, that make the problem of multi-angular classification harder and might lead to catastrophic results, since surfaces with the same reflectance return significantly different signals. In this paper, rather than performing atmospheric or bi-directional reflection distribution function (BRDF) correction, a non-linear manifold learning approach is used to align data structures. This method maximizes the similarity between the different acquisitions by deforming their manifold, thus enhancing the transferability of classification models among the images of the sequence.

Probe-specific mixed-model approach to detect copy number differences using multiplex ligation-dependent probe amplification (MLPA)

Background: MLPA method is a potentially useful semi-quantitative method to detect copy number alterations in targeted regions. In this paper, we propose a method for the normalization procedure based on a non-linear mixed-model, as well as a new approach for determining the statistical significance of altered probes based on linear mixed-model. This method establishes a threshold by using different tolerance intervals that accommodates the specific random error variability observed in each test sample.Results: Through simulation studies we have shown that our proposed method outperforms two existing methods that are based on simple threshold rules or iterative regression. We have illustrated the method using a controlled MLPA assay in which targeted regions are variable in copy number in individuals suffering from different disorders such as Prader-Willi, DiGeorge or Autism showing the best performace.Conclusion: Using the proposed mixed-model, we are able to determine thresholds to decide whether a region is altered. These threholds are specific for each individual, incorporating experimental variability, resulting in improved sensitivity and specificity as the examples with real data have revealed.

MEPDG Work Plan Task No. 5: Characterization of Unbound Materials (Soils/Aggregates) for Mechanistic-Empirical Pavement Design Guide, 2009

The resilient modulus (MR) input parameters in the Mechanistic-Empirical Pavement Design Guide (MEPDG) program have a significant effect on the projected pavement performance. The MEPDG program uses three different levels of inputs depending on the desired level of accuracy. The primary objective of this research was to develop a laboratory testing program utilizing the Iowa DOT servo-hydraulic machine system for evaluating typical Iowa unbound materials and to establish a database of input values for MEPDG analysis. This was achieved by carrying out a detailed laboratory testing program designed in accordance with the AASHTO T307 resilient modulus test protocol using common Iowa unbound materials. The program included laboratory tests to characterize basic physical properties of the unbound materials, specimen preparation and repeated load triaxial tests to determine the resilient modulus. The MEPDG resilient modulus input parameter library for Iowa typical unbound pavement materials was established from the repeated load triaxial MR test results. This library includes the non-linear, stress-dependent resilient modulus model coefficients values for level 1 analysis, the unbound material properties values correlated to resilient modulus for level 2 analysis, and the typical resilient modulus values for level 3 analysis. The resilient modulus input parameters library can be utilized when designing low volume roads in the absence of any basic soil testing. Based on the results of this study, the use of level 2 analysis for MEPDG resilient modulus input is recommended since the repeated load triaxial test for level 1 analysis is complicated, time consuming, expensive, and requires sophisticated equipment and skilled operators.

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Techniques for CT and MR, post-processing, radiation.

Brain perfusion can be assessed by CT and MR. For CT, two major techniquesare used. First, Xenon CT is an equilibrium technique based on a freely diffusibletracer. First pass of iodinated contrast injected intravenously is a second method,more widely available. Both methods are proven to be robust and quantitative,thanks to the linear relationship between contrast concentration and x-ray attenuation.For the CT methods, concern regarding x-ray doses delivered to the patientsneed to be addressed. MR is also able to assess brain perfusion using the firstpass of gadolinium based contrast agent injected intravenously. This method hasto be considered as a semi-quantitative because of the non linear relationshipbetween contrast concentration and MR signal changes. Arterial spin labelingis another MR method assessing brain perfusion without injection of contrast. Insuch case, the blood flow in the carotids is magnetically labelled by an externalradiofrequency pulse and observed during its first pass through the brain. Eachof this various CT and MR techniques have advantages and limits that will be illustratedand summarised.Learning Objectives:1. To understand and compare the different techniques for brain perfusionimaging.2. To learn about the methods of acquisition and post-processing of brainperfusion by first pass of contrast agent for CT and MR.3. To learn about non contrast MR methods (arterial spin labelling).

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Blind channel deconvolution of real world signals using source separation techniques

In this paper we present a method for blind deconvolution of linear channels based on source separation techniques, for real word signals. This technique applied to blind deconvolution problems is based in exploiting not the spatial independence between signals but the temporal independence between samples of the signal. Our objective is to minimize the mutual information between samples of the output in order to retrieve the original signal. In order to make use of use this idea the input signal must be a non-Gaussian i.i.d. signal. Because most real world signals do not have this i.i.d. nature, we will need to preprocess the original signal before the transmission into the channel. Likewise we should assure that the transmitted signal has non-Gaussian statistics in order to achieve the correct function of the algorithm. The strategy used for this preprocessing will be presented in this paper. If the receiver has the inverse of the preprocess, the original signal can be reconstructed without the convolutive distortion.