Matrix Crack Detection in Composite Plate with Spatially Random Material Properties using Fractal Dimension

Fractal dimension based damage detection method is investigated for a composite plate with random material properties. Composite material shows spatially varying random material properties because of complex manufacturing processes. Matrix cracks are considered as damage in the composite plate. Such cracks are often seen as the initial damage mechanism in composites under fatigue loading and also occur due to low velocity impact. Static deflection of the cantilevered composite plate with uniform loading is calculated using the finite element method. Damage detection is carried out based on sliding window fractal dimension operator using the static deflection. Two dimensional homogeneous Gaussian random field is generated using Karhunen-Loeve (KL) expansion to represent the spatial variation of composite material property. The robustness of fractal dimension based damage detection method is demonstrated considering the composite material properties as a two dimensional random field.

Sensitive detection of C-reactive protein using optical fiber Bragg gratings

An accurate and highly sensitive sensor platform has been demonstrated for the detection of C-reactive protein (CRP) using optical fiber Bragg gratings (FBGs). The CRP detection has been carried out by monitoring the shift in Bragg wavelength (Delta lambda(B)) of an etched FBG (eFBG) coated with an anti-CRP antibody (aCRP)-graphene oxide (GO) complex. The complex is characterized by Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy and atomic force microscopy. A limit of detection of 0.01 mg/L has been achieved with a linear range of detection from 0.01 mg/L to 100 mg/L which includes clinical range of CRP. The eFBG sensor coated with only aCRP (without GO) show much less sensitivity than that of aCRP-GO complex coated eFBG. The eFBG sensors show high specificity to CRP even in the presence of other interfering factors such as urea, creatinine and glucose. The affinity constant of similar to 1.1 x 10(10) M-1 has been extracted from the data of normalized shift (Delta lambda(B)/lambda(B)) as a function of CRP concentration. (C) 2014 Elsevier B.V. All rights reserved.

Multithreaded Test Synthesis for Deadlock Detection

Designing and implementing thread-safe multithreaded libraries can be a daunting task as developers of these libraries need to ensure that their implementations are free from concurrency bugs, including deadlocks. The usual practice involves employing software testing and/or dynamic analysis to detect. deadlocks. Their effectiveness is dependent on well-designed multithreaded test cases. Unsurprisingly, developing multithreaded tests is significantly harder than developing sequential tests for obvious reasons. In this paper, we address the problem of automatically synthesizing multithreaded tests that can induce deadlocks. The key insight to our approach is that a subset of the properties observed when a deadlock manifests in a concurrent execution can also be observed in a single threaded execution. We design a novel, automatic, scalable and directed approach that identifies these properties and synthesizes a deadlock revealing multithreaded test. The input to our approach is the library implementation under consideration and the output is a set of deadlock revealing multithreaded tests. We have implemented our approach as part of a tool, named OMEN1. OMEN is able to synthesize multithreaded tests on many multithreaded Java libraries. Applying a dynamic deadlock detector on the execution of the synthesized tests results in the detection of a number of deadlocks, including 35 real deadlocks in classes documented as thread-safe. Moreover, our experimental results show that dynamic analysis on multithreaded tests that are either synthesized randomly or developed by third-party programmers are ineffective in detecting the deadlocks.

Trace Driven Dynamic Deadlock Detection and Reproduction

Dynamic analysis techniques have been proposed to detect potential deadlocks. Analyzing and comprehending each potential deadlock to determine whether the deadlock is feasible in a real execution requires significant programmer effort. Moreover, empirical evidence shows that existing analyses are quite imprecise. This imprecision of the analyses further void the manual effort invested in reasoning about non-existent defects. In this paper, we address the problems of imprecision of existing analyses and the subsequent manual effort necessary to reason about deadlocks. We propose a novel approach for deadlock detection by designing a dynamic analysis that intelligently leverages execution traces. To reduce the manual effort, we replay the program by making the execution follow a schedule derived based on the observed trace. For a real deadlock, its feasibility is automatically verified if the replay causes the execution to deadlock. We have implemented our approach as part of WOLF and have analyzed many large (upto 160KLoC) Java programs. Our experimental results show that we are able to identify 74% of the reported defects as true (or false) positives automatically leaving very few defects for manual analysis. The overhead of our approach is negligible making it a compelling tool for practical adoption.

Matrix crack detection in spatially random composite structures using fractal dimension

Fractal dimension based damage detection method is studied for a composite structure with random material properties. A composite plate with localized matrix crack is considered. Matrix cracks are often seen as the initial damage mechanism in composites. Fractal dimension based method is applied to the static deformation curve of the structure to detect localized damage. Static deflection of a cantilevered composite plate under uniform loading is calculated using the finite element method. Composite material shows spatially varying random material properties because of complex manufacturing processes. Spatial variation of material property is represented as a two dimensional homogeneous Gaussian random field. Karhunen-Loeve (KL) expansion is used to generate a random field. The robustness of fractal dimension based damage detection methods is studied considering the composite plate with spatial variation in material properties.

Colorimetric detection of melamine based on the size effect of AuNPs

A simple colorimetric detection of melamine was studied using 15 nm (AuNPs-I), 30 nm (AuNPs-II), and 40 nm (AuNPs-III) citrate-capped gold nanoparticles (AuNPs). The AuNPs aggregated in aqueous solution in the presence of melamine, showing a visual color change from red to blue. This color change led to a shift in the absorption peak from 527 nm, 526 nm, and 525 nm to 638 nm, 626 nm, and 680 nm for AuNPs-I, AuNPs-II, and AuNPs-III, respectively. For all the three AuNPs, linearity was observed between the melamine concentration in aqueous solution and the absorbance ratios, A(638/527), A(626/525), and A(680/526), respectively. The limit of detection (LOD) for melamine for the AuNPs-II was found to be 2.37 x 10(-8) M (correlation coefficient R-2 = 0.9745), which showed better sensitivity as compared to the LOD of the AuNPs-I and AuNPs-III, which were 3.3 x 10(-8) M and 8.9 x 10(-8) M, respectively. The synthesis of AuNPs-II also involved a lower HAuCl4 concentration compared with the other two types of AuNPs, which may reduce the process cost. The AuNPs-II was selected to analyze melamine in pre-treated milk samples, and the recovery percentage was in the range of 91-106%. Thus, the efficient detection of melamine was possible using AuNPs-II for the on-site detection without the aid of expensive instruments.

Highly sensitive and rapid detection of acetylcholine using an ITO plate modified with platinum-graphene nanoparticles

Determining the concentrations of acetylcholine (ACh) and choline (Ch) is clinically important. ACh is a neurotransmitter that acts as a key link in the communication between neurons in the spinal cord and in nerve skeletal junctions in vertebrates, and plays an important role in transmitting signals in the brain. A bienzymatic sensor for the detection of ACh was prepared by co-immobilizing choline oxidase (ChO) and acetylcholinesterase (AChE) on graphene matrix/platinum nanoparticles, and then electrodepositing them on an ITO-coated glass plate. Graphene nanoparticles were decorated with platinum nanoparticles and were electrodeposited on a modified ITO-coated glass plate to form a modified electrode. The modified electrode was characterized by scanning electron microscopy (SEM), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) studies. The optimum response of the enzyme electrode was obtained at pH 7.0 and 35 degrees C. The response time of this ACh-sensing system was shown to be 4 s. The linear range of responses to ACh was 0.005-700 mu M. This biosensor exhibits excellent anti-interferential abilities and good stability, retaining 50% of its original current even after 4 months. It has been applied for the detection of ACh levels in human serum samples.

NrichD database: sequence databases enriched with computationally designed protein-like sequences aid in remote homology detection

NrichD ( ext-link-type=''uri'' xlink:href=''http://proline.biochem.iisc.ernet.in/NRICHD/'' xlink:type=''simple''>http://proline.biochem.iisc.ernet.in/NRICHD/)< /named-content> is a database of computationally designed protein-like sequences, augmented into natural sequence databases that can perform hops in protein sequence space to assist in the detection of remote relationships. Establishing protein relationships in the absence of structural evidence or natural `intermediately related sequences' is a challenging task. Recently, we have demonstrated that the computational design of artificial intermediary sequences/linkers is an effective approach to fill naturally occurring voids in protein sequence space. Through a large-scale assessment we have demonstrated that such sequences can be plugged into commonly employed search databases to improve the performance of routinely used sequence search methods in detecting remote relationships. Since it is anticipated that such data sets will be employed to establish protein relationships, two databases that have already captured these relationships at the structural and functional domain level, namely, the SCOP database and the Pfam database, have been `enriched' with these artificial intermediary sequences. NrichD database currently contains 3 611 010 artificial sequences that have been generated between 27 882 pairs of families from 374 SCOP folds. The data sets are freely available for download. Additional features include the design of artificial sequences between any two protein families of interest to the user.

Water-responsive carbon nanotubes for selective detection of toxic gases

Ammonia plays an important role in our daily lives and hence its quantitative and qualitative sensing has become necessary. Bulk structure of carbon nanotubes (CNTs) has been employed to detect the gas concentration of 10 ppm. Hydrophobic CNTs were turned to hydrophilic via the application of a ramp electric field that allowed confinement of a controlled amount of water inside CNT microstructure. These samples were then also used to detect different gases. A comparative study has been performed for sensing three reducing gases, namely, ammonia, sulphur-di-oxide, and hydrogen sulphide to elaborate the selectivity of the sensor. A considerable structural bending in the bulk CNT was observed on evaporation of the confined water, which can be accounted to the zipping of individual nanotubes. However, the rate of the stress induced on these bulk microstructures increased on the exposure of ammonia due to the change in the surface tension of the confined solvent. A prototype of an alarm system has been developed to illustrate sensing concept, wherein the generated stress in the bulk CNT induces a reversible loss in electrical contact that changes the equivalent resistance of the electrical circuit upon exposure to the gas. (C) 2015 AIP Publishing LLC.

Detection of G-Quadruplex DNA Using Primer Extension as a Tool

DNA sequence and structure play a key role in imparting fragility to different regions of the genome. Recent studies have shown that non-B DNA structures play a key role in causing genomic instability, apart from their physiological roles at telomeres and promoters. Structures such as G-quadruplexes, cruciforms, and triplexes have been implicated in making DNA susceptible to breakage, resulting in genomic rearrangements. Hence, techniques that aid in the easy identification of such non-B DNA motifs will prove to be very useful in determining factors responsible for genomic instability. In this study, we provide evidence for the use of primer extension as a sensitive and specific tool to detect such altered DNA structures. We have used the G-quadruplex motif, recently characterized at the BCL2 major breakpoint region as a proof of principle to demonstrate the advantages of the technique. Our results show that pause sites corresponding to the non-B DNA are specific, since they are absent when the G-quadruplex motif is mutated and their positions change in tandem with that of the primers. The efficiency of primer extension pause sites varied according to the concentration of monovalant cations tested, which support G-quadruplex formation. Overall, our results demonstrate that primer extension is a strong in vitro tool to detect non-B DNA structures such as G-quadruplex on a plasmid DNA, which can be further adapted to identify non-B DNA structures, even at the genomic level.

Analyzing the kinetic response of tin oxide-carbon and tin oxide-CNT composites gas sensors for alcohols detection

Tin oxide nanoparticles are synthesized using solution combustion technique and tin oxide - carbon composite thick films are fabricated with amorphous carbon as well as carbon nanotubes (CNTs). The x-ray diffraction, Raman spectroscopy and porosity measurements show that the as-synthesized nanoparticles are having rutile phase with average crystallite size similar to 7 nm and similar to 95 m(2)/g surface area. The difference between morphologies of the carbon doped and CNT doped SnO2 thick films, are characterized using scanning electron microscopy and transmission electron microscopy. The adsorption-desorption kinetics and transient response curves are analyzed using Langmuir isotherm curve fittings and modeled using power law of semiconductor gas sensors. (C) 2015 Author(s).

Electron-Rich Triphenylamine-Based Sensors for Picric Acid Detection

This paper demonstrates the role of solvent in selectivity and sensitivity of a series of electron-rich compounds for the detection of trace amounts of picric acid. Two new electron-rich fluorescent esters (6, 7) containing a triphenylamine backbone as well as their analogous carboxylic acids (8, 9) have been synthesized and characterized. Fluorescent triphenylamine coupled with an ethynyl moiety constitutes p-electron-rich selective and sensitive probes for electron-deficient picric acid (PA). In solution, the high sensitivity of all the sensors toward PA can be attributed to a combined effect of the ground-state charge-transfer complex formation and resonance energy transfer between the sensor and analyte. The acids 8 and 9 also showed enhanced sensitivity for nitroaromatics in the solid state, and their enhanced sensitivity could be attributed to exciton migration due to close proximity of the neighboring acid molecules, as evident from the X-ray diffraction study. The compounds were found to be quite sensitive for the detection of trace amount of nitroaromatics in solution, solid, and contact mode.

Synthesis of cadmium oxide and carbon nanotube based nanocomposites and their use as a sensing interface for xanthine detection

Xanthine oxidase (XOD) extracted from bovine milk was immobilized covalently via N-ethyl-N'-(3-dimethylaminopropyl) carbodiimide (EDC) and N-hydroxy succinimide (NHS) chemistry onto cadmium oxide nanoparticles (CdO)/carboxylated multiwalled carbon nanotube (c-MWCNT) composite film electrodeposited on the surface of an Au electrode. The nanocomposite modified Au electrode was characterized by Fourier transform infrared (FTIR), cyclic voltammetry (CV), scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS) before and after immobilization of XOD. Under optimal operation conditions (25 degrees C, + 0.2 V vs. Ag/AgCl, sodium phosphate buffer, pH 7.5), the following characteristics are attributed to the biosensor: linearity of response up to xanthine concentrations of 120 mu M, detection limit of 0.05 mu M (S/N = 3) and a response time of at most 4 s. After being used 100 times over a period of 120 days, only 50% loss of the initial activity of the biosensor was evaluated when stored at 4 degrees C. The fabricated biosensor was successfully employed for the determination of xanthine in fish meat.

Postsynthetic Exterior Decoration of an Organic Cage by Copper(I)-Catalysed A(3)-Coupling and Detection of Nitroaromatics

A new synthetic protocol based on one-pot, copper(I)-catalysed multicomponent reaction of formaldehyde, secondary amine and terminal alkyne has been employed to postsynthetically modify a self-assembled nanoscopic organic cage. By employing this synthetic strategy, three new cages appended with phenyl-, xylyl-and naphthyl-acetylene moieties have been synthesised. The resulting modified cages were characterised by using a range of spectroscopic techniques. The synthesised cages were fluorescent and thus one of them was tested to explore the potential use of such compounds as chemosensors for the detection of nitroaromatics. Experimental findings suggest a high selective quenching of initial fluorescence intensity in the presence of nitroaromatic compounds. Furthermore, it has been observed that among the various nitroaromatics tested, nitrophenolic compounds have better quenching ability.

Polyfunctional Lewis Acids: Intriguing Solid-State Structure and Selective Detection and Discrimination of Nitroaromatic Explosives

Synthesis and crystal structures of three porphyrin-based polyfunctional Lewis acids 1-3 are reported. Intermolecular HgClHgCl (linear and -type) interactions in the solid state of the peripherally ArHgCl-decorated compound 3 lead to a fascinating 3D supramolecular architecture. Compound3 shows a selective fluorescence quenching response to picric acid and discriminates other nitroaromatic-based explosives. For the first time, an electron-deficient polyfunctional Lewis acid is shown to be useful for the selective detection and discrimination of nitroaromatic explosives. The Stern-Volmer quenching constant and detection limits of compound3 for picric acid are the best among the reported small-molecular receptors for nitroaromatic explosives. The electronic structure, Lewis acidity, and selective sensing characteristics of 3 are well corroborated by DFT calculations.