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

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

Polyphenolic contents of natural dyes produced from industrial plants assayed by HPLC and novel spectrophotometric methods

Polyphenolic compounds are abundantly found in natural dyes. The cupric reducing antioxidant capacity assay originally developed in our laboratories was utilized to estimate the total polyphenolic content of natural dyes (i.e., Rubia tinctorum L, Curcuma longa L., Alkanna tinctoria, Matricaria chamomilla, Dactylopius coccus Costa) for the first time. The polyphenolic compounds such as ellagic acid, gallic acid, quercetin, rutin, fisetin, myricetin, kaempferol, luteolin, apigenin, and morin were all capable of reducing the Cu(II)-neocuproine reagent to the Cu(I)-neocuproine chelate showing maximum absorbance at 450 nm, and the responses of synthetic mixture components were additive in accordance with Beer's law. As a comparative reference method, the AlCl3/potassium acetate spectrophotometric method was applied to total flavonoid assay of these dyes. The results of the proposed and reference methods were correlated with high performance liquid chromatography (HPLC) findings expressed in the units of quercetin (QR) equivalent polyphenolic concentration. The individual phenolic constituents of dye extracts were identified and quantified by HPLC on a C18 column (alizarin, curcumin, carminic acid, etc.). The method of standard additions was applied to the solutions of these dyes by adding standard increments of QR and measuring the resulting absorbances. (C) 2010 Elsevier B.V. All rights reserved

Antioxidant/antiradical properties of microwave-assisted extracts of three wild edible mushrooms

A microwave-assisted extraction (MAE) process for polyphenols from three wild edible mushrooms was studied. The optimal extraction conditions were found to be methanol concentration of 80%, extraction temperature of 80 degrees C, and extraction time of 5 min. Different antioxidant assays (i.e., total antioxidant capacity (TAC) and total phenolic content (TPC)) were utilized to evaluate the antioxidant capacity of the methanolic extracts of Terfezia boudieri Chatin, Boletus edulis, and Lactarius volemus. The reactive species scavenging activities of these extracts were also investigated in vitro. High contents of phenolic and flavonoid compounds may be the major contributors to the observed high antioxidant activities of these extracts. B. edulis showed the higher TAC and TPC; highest inhibitory effect on DPPH and on other studied reactive oxygen species (ROS). MAE showed obvious advantages of high extraction efficiency with lower solvent consumption in terms of high antioxidant capacity/activity of extracts achieved within the shortest time. (C) 2014 Elsevier Ltd. All rights reserved

Novel Optical Fiber Reflectometric CUPRAC Sensor for Total Antioxidant Capacity Measurement of Food Extracts and Biological Samples

A novel fiber optic sensor was developed for screening the total antioxidant capacity (TAC) based on the use of cupricneocuproine (Cu(II)Nc) immobilized onto a Nafion cation-exchange membrane with reflectance spectrometric measurement. The reflectance change associated with the formation of the highly colored Cu(I)Nc chelate on the membrane as a result of reaction with antioxidants was measured at 530 nm by using a miniature reflectance spectrometer. The calibration graph of trolox (TR) was linear with a slope of 3.40 x 10(3) L mol(-1) mm(-1). The limit of detection (LOD) and limit of quantification (LOQ) for TR in the reflectometric cupric reducing antioxidant capacity (CUPRAC) method were found as 0.53 and 1.76 mu M, respectively. The trolox equivalent antioxidant capacities (TEAC) of various antioxidant compounds using the proposed method were comparable to those of the main CUPRAC assay. This assay was validated through linearity, additivity, precision, and recovery. The developed reflectance sensor was used to screen the TAC of some commercial fruit juices and mice tissue homogenates without preliminary treatment. The method is rapid, inexpensive, versatile, and nonlaborious, uses stable reagents on the sensor, and enables the in situ estimation of antioxidant capacity of food extracts and biological samples

Development of a Low-Cost Optical Sensor for Cupric Reducing Antioxidant Capacity Measurement of Food Extracts

A low-cost optical sensor using an immobilized chromogenic redox reagent was devised for measuring the total antioxidant level in a liquid sample without requiring sample pretreatment. The reagent, copper(II) neocuproine (Cu(II)-Nc) complex, was immobilized onto a cation-exchanger film of Nafion, and the absorbance changes associated with the formation of the highly colored Cu(I)-Nc chelate as a result of reaction with antioxidants was measured at 450 nm. The sensor gave a linear response over a wide concentration range of standard antioxidant compounds. The trolox equivalent antioxidant capacity (TEAC) values of various antioxidants reported in this work using the optical sensor-based "cupric reducing antioxidant capacity" (CUPRAC) assay were comparable to those of the standard solution-based CUPRAC assay, showing that the immobilized Cu(II)-Nc reagent retained its reactivity toward antioxidants. Common food ingredients like oxalate, citrate, fruit acids, and reducing sugars did not interfere with the proposed sensing method. This assay was validated through linearity, additivity, precision, and recovery, demonstrating that the assay is reliable and robust. The developed optical sensor was used to screen total antioxidant capacity (TAC) of some commercial fruit juices without preliminary treatment and showed a promising potential for the preparation of antioxidant inventories of a wide range of food plants

Optimization of Microwave-Assisted Extraction of Curcumin from Curcuma longa L. (Turmeric) and Evaluation of Antioxidant Activity in Multi-Test Systems

Turmeric (Curcuma longa L.) is a medicinal plant, and its biological activities mainly arise from the main constituent, known as diferuloylmethane or curcumin. In the present paper, microwave-assisted extraction (MAE) was investigated for the recovery of curcumin from turmeric in comparison to conventional heat-assisted extraction (CHAE) technique. Various experimental conditions, such as solvent concentration (0-100%, v/v), MAE temperature (30-130 degrees C) and MAE time (0-20 min) were investigated to optimize the extraction of curcumin from turmeric. The identification and quantification of curcumin in extracts were performed by HPLC-DAD system. Antioxidant potential and radical scavenging abilities of microwave-assisted extract and conventional heat-assisted extract of turmeric (MAET and CHAET) were evaluated using different systems including total phenolic content (TPC), total antioxidant capacity (TAC), and radical scavenging activities. MAET and CHAET showed high antioxidant activity in all test systems, but the antioxidant properties of MAET were stronger than those of CHAET

The main and modified CUPRAC methods of antioxidant measurement

The antioxidant activity/capacity levels of biological fluids and foods are measured for the diagnosis and the treatment of oxidative stress-associated diseases in clinical biochemistry, and for meaningful comparison of the antioxidant content of foods. Currently, there is no "total antioxidant" as a nutritional index available for food labeling and biological fluids due to the lack of standardized quantitative methods