Advanced Approaches to Characterizing Nonlinear Pavement System Responses

The use of falling weight deflectometer—based backcalculation techniques to determine pavement layer moduli is a cost-effective and widely used method for the structural evaluation of an existing pavement. The nonlinear stress-sensitive response of pavement geomaterials has been well established, and mechanistic-based pavement design can be improved by inclusion of these nonlinear material properties. To further the science of nonlinear backcalculation, the TRB Strength and Deformation Characteristics of Pavement Sections Committee has assembled four data sets that can be used to demonstrate the ability to derive stress-dependent moduli for pavement layers. In this study, validated artificial neural network (ANN)—based backcalculation-type flexible pavement analysis models were used to evaluate the TRB Nonlinear Pavement Analysis Project data sets. The Illi-Pave finite element (FE) model, considering nonlinear stress-dependent geomaterials characterization, was utilized to generate a solution database for developing the ANN-based structural models. Such use of ANN models enables the incorporation of needed sophistication in structural analysis, such as FE modeling with proper materials characterization, into routine practical design. This study illustrated the complexities associated with interpreting the backcalculated modulus values. In general, the predicted strains agreed reasonably well with the measured strain values, whereas the predicted stresses did not

Airfield pavement deterioration assessment using stress-dependent neural network models

In this study, an artificial neural network (ANN)-based approach was employed to backcalculate the asphalt concrete and non-linear stress-dependent subgrade moduli from non-destructive test (NDT) data acquired at the Federal Aviation Administration\u27s National Airport Pavement Test Facility (NAPTF) during full-scale traffic testing. The ANN models were trained with results from an axisymmetric finite element pavement structural model. Using the ANN-predicted moduli based on the NDT test results, the relative severity effects of simulated Boeing 777 (B777) and Boeing 747 (B747) aircraft gear trafficking on the structural deterioration of NAPTF flexible pavement test sections were characterized. The results indicate the potential of using lower force amplitude NDT test data for routine airport pavement structural evaluation, as long as they generate sufficient deflections for reliable data acquisition. Therefore, NDT tests that employ force amplitudes at prototypical aircraft loading may not be necessary to evaluate airport pavements

Noise-tolerant inverse analysis models for nondestructive evaluation of transportation infrastructure systems using neural networks

The need to rapidly and cost-effectively evaluate the present condition of pavement infrastructure is a critical issue concerning the deterioration of ageing transportation infrastructure all around the world. Nondestructive testing (NDT) and evaluation methods are well-suited for characterising materials and determining structural integrity of pavement systems. The falling weight deflectometer (FWD) is a NDT equipment used to assess the structural condition of highway and airfield pavement systems and to determine the moduli of pavement layers. This involves static or dynamic inverse analysis (referred to as backcalculation) of FWD deflection profiles in the pavement surface under a simulated truck load. The main objective of this study was to employ biologically inspired computational systems to develop robust pavement layer moduli backcalculation algorithms that can tolerate noise or inaccuracies in the FWD deflection data collected in the field. Artificial neural systems, also known as artificial neural networks (ANNs), are valuable computational intelligence tools that are increasingly being used to solve resource-intensive complex engineering problems. Unlike the linear elastic layered theory commonly used in pavement layer backcalculation, non-linear unbound aggregate base and subgrade soil response models were used in an axisymmetric finite element structural analysis programme to generate synthetic database for training and testing the ANN models. In order to develop more robust networks that can tolerate the noisy or inaccurate pavement deflection patterns in the NDT data, several network architectures were trained with varying levels of noise in them. The trained ANN models were capable of rapidly predicting the pavement layer moduli and critical pavement responses (tensile strains at the bottom of the asphalt concrete layer, compressive strains on top of the subgrade layer and the deviator stresses on top of the subgrade layer), and also pavement surface deflections with very low average errors comparable with those obtained directly from the finite element analyses

Sensitivity analysis of rigid pavement systems using the mechanistic-empirical design guide software

Initiatives are underway to implement the new mechanistic-empirical pavement design guide (MEPDG) in Iowa. This paper focuses on the sensitivity study of jointed plain concrete pavements (JPCP) and continuously reinforced concrete pavements (CRCP) in Iowa using the MEPDG software. In this comprehensive study, the effect of MEPDG input parameters on the rigid pavement performance is evaluated using the different versions of the MEPDG software (0.7, 0.9, and 1.0) available to date. Representative JPCP and CRCP sections in Iowa were selected for analysis. Based on the sensitivity plots obtained from the MEPDG runs, the design input parameters were categorized as being most sensitive, moderately sensitive, or least sensitive in terms of their relative effect on distresses. In this study, the curl/warp effective temperature difference, the PCC coefficient of thermal expansion, and PCC thermal conductivity had the greatest impact on the JPCP and CRCP distresses. Compared to the original version of MEPDG software (Version 0.7), the updated versions (Versions 0.9 and 1.0) are more sensitive to inputs, which shows the evolution of engineering reasonableness

Optimization of a pulsed-field gel electrophoresis for molecular typing of Proteus mirabilis

Objective: For the detection of outbreaks caused byProteus mirabilis, strains clonal relations are determinedmethods as “pulsed-field gel electrophoresis (PFGE)”.The aim of this study was optimization of a pulsed-fieldgel electrophoresis for molecular typing of P. mirabilis.Methods: In this study, PFGE’ protocol is optimized foruse in molecular typing of P. mirabilis. Phylogenetic analyzesof strains were evaluated with Bionumerics softwaresystem (version 6.01; Applied Maths, Sint-Martens-Latem, Belgium).Results: This protocol compared with Gram-negativebacteria PFGE protocols, NotI enzyme is suitable for thisbacterium. Electrophoresis conditions should be revealedas; - block 1: initial pulse duration 1 sec, ending pulseduration 30 sec, striking angle 120°, the current 6 V/cm2,temperature 14°C, time 8 hours; - block 2: initial pulseduration 30 sec, ending pulse duration 70 sec, strikingangle 120°, the current 6 V/cm2, temperature 14°C, time16 hours; - TBE, pH=8.4.Conclusion: P. mirabilis strains were typed by PFGE andBionumerics analysis program were determined clonal relationships.The procedure was simple, reproducible andsuitable for these bacteria. Also it was evaluated, becauseof reducing time, the solution volumes and enzymes canbe economically. Outbreaks of nosocomial infections dueto bacteria studied assessment and the potential to provideuseful information about the degree of prevalence.This optimized protocol is allowed different centers’ PFGEresults to compare with other laboratories results. J ClinExp Invest 2013; 4 (3): 306-312Key words: Proteus mirabilis, molecular typing, pulsedfieldgel electrophoresis

Nondestructive Evaluation of Iowa Pavements-Phase I

Evaluating structural conditions of existing, in-service pavements is a part of the routine maintenance and rehabilitation activities undertaken by the most departments of transportation (DOTs). In the field, the pavement deflection profiles (or basins) gathered from the nondestructive falling weight deflectometer (FWD) test data are typically used to evaluate pavement structural conditions. Over the past decade, interest has increased in a new class of computational intelligence system, known as artificial neural networks (ANNs), for use in geomechanical and pavement systems applications. This report describes the development and use of ANN models as pavement structural analysis tools for the rapid and accurate prediction of layer parameters of Iowa pavements subjected to typical highway loadings. ANN models trained with the results from the structural analysis program solutions have been found to be practical alternatives. The ILLI-PAVE, ISLAB2000, and DIPLOMAT programs were used as the structural response models for solving the deflection parameters of flexible, rigid, and composite pavements, respectively. The trained ANN models in this study were capable of predicting pavement layer moduli and critical pavement responses from FWD deflection basins with low errors. The developed methodology was successfully verified using results from long-term pavement performance (LTPP) FWD tests, as well as Iowa DOT FWD field data. All successfully developed ANN models were incorporated into a Microsoft Excel spreadsheet-based backcalculation software toolbox with a user-friendly interface. The final outcome of this study was a field-validated, nondestructive pavement evaluation toolbox that will be used to assess pavement condition, estimate remaining pavement life, and eventually help assess pavement rehabilitation strategies by the Iowa DOT pavement management team

Non-Destructive Evaluation of Iowa Pavements Phase 2: Development of a Fully Automated Software System for Rapid Analysis/Processing of the Falling Weight Deflectometer Data

The Office of Special Investigations at Iowa Department of Transportation (DOT) collects FWD data on regular basis to evaluate pavement structural conditions. The primary objective of this study was to develop a fully-automated software system for rapid processing of the FWD data along with a user manual. The software system automatically reads the FWD raw data collected by the JILS-20 type FWD machine that Iowa DOT owns, processes and analyzes the collected data with the rapid prediction algorithms developed during the phase I study. This system smoothly integrates the FWD data analysis algorithms and the computer program being used to collect the pavement deflection data. This system can be used to assess pavement condition, estimate remaining pavement life, and eventually help assess pavement rehabilitation strategies by the Iowa DOT pavement management team. This report describes the developed software in detail and can also be used as a user-manual for conducting simulation studies and detailed analyses

Evaluation of clinical efficacy of gamithromycin in the treatment of naturally infected neonatal calves with cryptosporidiosis

Aim: The purpose of this study was to investigate the clinical efficacy of gamithromycin in the treatment of naturally infected neonatal calves with cryptosporidiosis. Materials and Methods: 5-20 days old 20 diarrheic neonatal calves were used as material in this study. Diagnosis of cryptosporidiosis was made by microscopic examination and ELISA test. Calves shedding Cryptosporidium oocysts between 4 x 104 and 15 x 106 per gram in feces were included in the study. Hemogram and blood gases were measured at the beginning of the treatment and after the treatment. A single dose of 6 mg/kg body weight of gamithromycin was administered subcutaneously. Drug efficacy was assessed by evaluating the existence of diarrhea, oocyst shedding and body condition from day 1 to 5. Results: On 5th day, the medicated 6 calves had no oocysts, and number of oocysts in feces had been decreased in 11 calves on 5th day. Statistically significant difference (p<0.05) was observed in the blood values at the beginning of the treatment and after the treatment. Conclusion: It has been determined that based on both clinical improvement and decrease in oocyst count in feces, gamithromycin was found to have moderate effect in the treatment of cryptosporidiosis in naturally infected neonatal calves

Protective and therapeutic effects of milrinone on acoustic trauma in rat cochlea

Objective: The aim of this study was to investigate the potential protective and therapeutic effects of milrinone, a specific phosphodiesterase (PDE) III inhibitor, on acoustic trauma-induced cochlear injury and apoptosis. Methods: A total number of 30 healthy Wistar albino rats were evenly divided into five groups as follows: group 1 was assigned as control group; group 2 and 3 were assigned as low-dosage groups (0.25 mg/kg) in which milrinone was administered 1 h before acoustic trauma (AT) and 2 h after AT, respectively; group 4 and 5 were assigned as high-dosage groups (0.50 mg/kg) in which the drug was administered 1 h before AT and 2 h after AT, respectively. Except control group, all treatment groups received a single dosage of milrinone for 5 days. Distortion product otoacoustic emissions (DPOAE) measurements were recorded before AT as well as at second and fifth post-traumatic days. At the end of fifth day, all rats were sacrificed and the cochlea of the rats was removed for histopathological evaluation. In addition, the groups were compared in terms of apoptotic index via caspase-3 staining. Results: In terms of signal-to-noise ratio (SNR), there was no statistically significant difference among the groups following AT (p > 0.05). After 5 days of milrinone treatment, the best SNR values were found in group 5, though all groups did not statistically differ (p > 0.05). In histopathological evaluation, vacuolization, inflammation, and edema scores in all treatment groups were statistically lower than those of the control group (p < 0.05). In group 2 and 4 where the drug was administered before AT, the inflammation and apoptosis index was lower than those of group 3 and 5 where the drug was administered after AT (p < 0.0001). Conclusion: We reveal that milrinone has a protective effect on cochlear damage in the experimental acoustic model of rats. This protective effect was more apparent following the pre-traumatic milrinone administration, and is associated with its effect on decreasing inflammation and apoptosis. Based on DPOAE measurements following AT, especially in the group 5 (high-dosage group), milrinone may also have a therapeutic effect

Diagnostic performance and interobserver agreement of CO-RADS: evaluation of classification in radiology practice

PURPOSEWe aimed to evaluate the use of the COVID-19 reporting and data system (CO-RADS) among radiologists and the diagnostic performance of this system.METHODSFour radiologists retrospectively evaluated the chest CT examinations of 178 patients. The study included 143 patients with positive reverse transcriptase-polymerase chain reaction (RT-PCR) test results and 35 patients whose RT-PCR tests were negative but whose clinical and/or radiological findings were consistent with COVID-19. Fleiss’ kappa (κ) values were calculated, and individual observers’ scores were compared. To investigate diagnostic efficiency, receiver operating characteristic (ROC) curves were calculated for each interpreter.RESULTSThe interpreters were in full agreement on 574 of 712 (80.6%) evaluations. The common Fleiss’ κ value of all the radiologists combined was 0.712 (95% confidence interval [CI] 0.692–0.769). A reliable prediction on the basis of RT-PCR and clinical findings indicated the mean area under the curve (AUC) of Fleiss’ κ value as 0.89 (95% CI 0.708–0.990). General interpreter agreement was found to range from moderate to good.CONCLUSIONThe interpreter agreement for CO-RADS categories 1 and 5 was reasonably good. We conclude that this scoring system will make a valuable contribution to efforts in COVID-19 diagnosis. CO-RADS can also be of significant value for the diagnosis and treatment of the disease in cases with false-negative PCR results