Rapid and sensitive measurements of nitrate ester explosives using microchip electrophoresis with electrochemical detection

This article describes an effective microchip protocol based on electrophoretic-separation and electrochemical detection for highly sensitive and rapid measurements of nitrate ester explosives, including ethylene glycol dinitrate (EGDN), pentaerythritol tetranitrate (PETN), propylene glycol dinitrate (PGDN) and glyceryl trinitrate (nitroglycerin, NG). Factors influencing the separation and detection processes were examined and optimized. Under the optimal separation conditions obtained using a 15 mM borate buffer (pH 9.2) containing 20 mM SDS, and applying a separation voltage of 1500 V, the four nitrate ester explosives were separated within less than 3 min. The glassy-carbon amperometric detector (operated at -0.9 V vs. Ag/AgCl) offers convenient cathodic detection down to the picogram level, with detection limits of 0.5 ppm and 0.3 ppm for PGDN and for NG, respectively, along with good repeatability (RSD of 1.8-2.3%; n = 6) and linearity (over the 10-60 ppm range). Such effective microchip operation offers great promise for field screening of nitrate ester explosives and for supporting various counter-terrorism surveillance activities.

Rapid prototyping of polymeric electrophoresis microchips with integrated copper electrodes for contactless conductivity detection

A simple and easy approach to produce polymeric microchips with integrated copper electrodes for capacitively coupled contactless conductivity detection (CD) is described. Copper electrodes were fabricated using a printed circuit board (PCB) as an inexpensive thin-layer of metal. The electrode layout was first drawn and laser printed on a wax paper sheet. The toner layer deposited on the paper sheet was thermally transferred to the PCB surface working as a mask for wet chemical etching of the copper layer. After the etching step, the toner was removed with an acetonitrile-dampened cotton. A poly(ethylene terephthalate) (PET) film coated with a thin thermo-sensitive adhesive layer was used to laminate the PCB plate providing an insulator layer of the electrodes to perform CID measurements. Electrophoresis microchannels were fabricated in poly(dimethylsiloxane) (PDMS) by soft lithography and reversibly sealed against the PET film. These hybrid PDMS/PET chips exhibited a stable electroosmotic mobility of 4.25 +/- 0.04 x 10(-4) V cm(-2) s(-1), at pH 6.1, over fifty runs. Efficiencies ranging from 1127 to 1690 theoretical plates were obtained for inorganic cations.

A NOVEL EPIPHYTIC CYANOBACTERIAL SPECIES FROM THE GENUS BRASILONEMA CAUSING DAMAGE TO EUCALYPTUS LEAVES

A cyanobacterial mat colonizing the leaves of Eucalyptus grandis was determined to be responsible for serious damage affecting the growth and development of whole plants under the clonal hybrid nursery conditions. The dominant cyanobacterial species was isolated in BG-11 medium lacking a source of combined nitrogen and identified by cell morphology characters and molecular phylogenetic analysis (16S rRNA gene and cpcBA-IGS sequences). The isolated strain represents a novel species of the genus Brasilonema and is designated Brasilonema octagenarum strain UFV-E1. Thin sections of E. grandis leaves analyzed by light and electron microscopy showed that the B. octagenarum UFV-E1 filaments penetrate into the leaf mesophyll. The depth of infection and the mechanism by which the cyanobacterium invades leaf tissue were not determined. A major consequence of colonization by this cyanobacterium is a reduction in photosynthesis in the host since the cyanobacterial mats decrease the amount of light incident on leaf surfaces. Moreover, the cyanobacteria also interfere with stomatal gas exchange, decreasing CO2 assimilation. To our knowledge, this is the first report of an epiphytic cyanobacterial species causing damage to E. grandis leaves.

Experimental chronic low-frequency resistance training produces skeletal muscle hypertrophy in the absence of muscle damage and metabolic stress markers

Volitional animal resistance training constitutes an important approach to modeling human resistance training. However, the lack of standardization protocol poses a frequent impediment to the production of skeletal muscle hypertrophy and the study of related physiological variables (i.e., cellular damage/inflammation or metabolic stress). Therefore, the purposes of the present study were: (1) to test whether a long-term and low frequency experimental resistance training program is capable of producing absolute increases in muscle mass; (2) to examine whether cellular damage/inflammation or metabolic stress is involved in the process of hypertrophy. In order to test this hypothesis, animals were assigned to a sedentary control (C, n = 8) or a resistance trained group (RT, n = 7). Trained rats performed 2 exercise sessions per week (16 repetitions per day) during 12 weeks. Our results demonstrated that the resistance training strategy employed was capable of producing absolute mass gain in both soleus and plantaris muscles (12%, p<0.05). Furthermore, muscle tumor necrosis factor (TNF-alpha) protein expression (soleus muscle) was reduced by 24% (p<0.01) in trained group when compared to sedentary one. Finally, serum creatine kinase (CK) activity and serum lactate concentrations were not affected in either group. Such information may have practical applications if reproduced in situations where skeletal muscle hypertrophy is desired but high mechanical stimuli of skeletal muscle and inflammation are not. Copyright (C) 2010 John Wiley & Sons, Ltd.

Effect of eccentric contraction velocity on muscle damage in repeated bouts of elbow flexor exercise

Eccentric exercise induces muscle damage, but controversy exists concerning the effect of contraction velocity on the magnitude of muscle damage, and little is known about the effect of contraction velocity on the repeated-bout effect. This study examined slow (60 degrees.s(-1)) and fast (180 degrees.s(-1)) velocity eccentric exercises for changes in indirect markers of muscle damage following 3 exercise bouts that were performed every 2 weeks. Fifteen young men were divided into 2 groups based on the velocity of eccentric exercise: 7 in the Ecc60 (60 degrees.s(-1)) group, and 8 in the Ecc180 (180 degrees.s(-1)) group. The exercise consisted of 30 maximal eccentric contractions of the elbow flexors at each velocity, in which the elbow joint was forcibly extended from 60 degrees to 180 degrees (full extension) on an isokinetic dynamometer. Changes in maximal voluntary isometric contraction strength, range of motion, muscle soreness, and plasma creatine kinase activity before and for 4 days after the exercise were compared in the 2 groups using a mixed-model analysis (group x bout x time). No significant differences between groups were evident for changes in any variables following exercise bouts; however, the changes were significantly smaller (p < 0.05) after the second and third bouts than after the first bout. These results indicate that the contraction velocity does not influence muscle damage or the repeated-bout effect.

Offline Detection, Identification, and Correction of Branch Parameter Errors Based on Several Measurement Snapshots

This paper proposes a three-stage offline approach to detect, identify, and correct series and shunt branch parameter errors. In Stage 1 the branches suspected of having parameter errors are identified through an Identification Index (II). The II of a branch is the ratio between the number of measurements adjacent to that branch, whose normalized residuals are higher than a specified threshold value, and the total number of measurements adjacent to that branch. Using several measurement snapshots, in Stage 2 the suspicious parameters are estimated, in a simultaneous multiple-state-and-parameter estimation, via an augmented state and parameter estimator which increases the V - theta state vector for the inclusion of suspicious parameters. Stage 3 enables the validation of the estimation obtained in Stage 2, and is performed via a conventional weighted least squares estimator. Several simulation results (with IEEE bus systems) have demonstrated the reliability of the proposed approach to deal with single and multiple parameter errors in adjacent and non-adjacent branches, as well as in parallel transmission lines with series compensation. Finally the proposed approach is confirmed on tests performed on the Hydro-Quebec TransEnergie network.

Fault Detection in Power Distribution Systems Using Automated Integration of Computational Intelligence Tools

The main purpose of this paper is to present architecture of automated system that allows monitoring and tracking in real time (online) the possible occurrence of faults and electromagnetic transients observed in primary power distribution networks. Through the interconnection of this automated system to the utility operation center, it will be possible to provide an efficient tool that will assist in decisionmaking by the Operation Center. In short, the desired purpose aims to have all tools necessary to identify, almost instantaneously, the occurrence of faults and transient disturbances in the primary power distribution system, as well as to determine its respective origin and probable location. The compilations of results from the application of this automated system show that the developed techniques provide accurate results, identifying and locating several occurrences of faults observed in the distribution system.

Innovation concept for measurement gross error detection and identification in power system state estimation

In this study, the innovation approach is used to estimate the measurement total error associated with power system state estimation. This is required because the power system equations are very much correlated with each other and as a consequence part of the measurements errors is masked. For that purpose an index, innovation index (II), which provides the quantity of new information a measurement contains is proposed. A critical measurement is the limit case of a measurement with low II, it has a zero II index and its error is totally masked. In other words, that measurement does not bring any innovation for the gross error test. Using the II of a measurement, the masked gross error by the state estimation is recovered; then the total gross error of that measurement is composed. Instead of the classical normalised measurement residual amplitude, the corresponding normalised composed measurement residual amplitude is used in the gross error detection and identification test, but with m degrees of freedom. The gross error processing turns out to be very simple to implement, requiring only few adaptations to the existing state estimation software. The IEEE-14 bus system is used to validate the proposed gross error detection and identification test.

Assessment of the Performance of Acoustic and Mass Balance Methods for Leak Detection in Pipelines for Transporting Liquids

On-line leak detection is a main concern for the safe operation of pipelines. Acoustic and mass balance are the most important and extensively applied technologies in field problems. The objective of this work is to compare these leak detection methods with respect to a given reference situation, i.e., the same pipeline and monitoring signals acquired at the inlet and outlet ends. Experimental tests were conducted in a 749 m long laboratory pipeline transporting water as the working fluid. The instrumentation included pressure transducers and electromagnetic flowmeters. Leaks were simulated by opening solenoid valves placed at known positions and previously calibrated to produce known average leak flow rates. Results have clearly shown the limitations and advantages of each method. It is also quite clear that acoustics and mass balance technologies are, in fact, complementary. In general, an acoustic leak detection system sends out an alarm more rapidly and locates the leak more precisely, provided that the rupture of the pipeline occurs abruptly enough. On the other hand, a mass balance leak detection method is capable of quantifying the leak flow rate very accurately and of detecting progressive leaks.

Leak detection by inverse transient analysis in an experimental PVC pipe system

Leakage reduction in water supply systems and distribution networks has been an increasingly important issue in the water industry since leaks and ruptures result in major physical and economic losses. Hydraulic transient solvers can be used in the system operational diagnosis, namely for leak detection purposes, due to their capability to describe the dynamic behaviour of the systems and to provide substantial amounts of data. In this research work, the association of hydraulic transient analysis with an optimisation model, through inverse transient analysis (ITA), has been used for leak detection and its location in an experimental facility containing PVC pipes. Observed transient pressure data have been used for testing ITA. A key factor for the success of the leak detection technique used is the accurate calibration of the transient solver, namely adequate boundary conditions and the description of energy dissipation effects since PVC pipes are characterised by a viscoelastic mechanical response. Results have shown that leaks were located with an accuracy between 4-15% of the total length of the pipeline, depending on the discretisation of the system model.

Wavelet-Galerkin method for one-dimensional elastoplasticity and damage problems: Constitutive modeling and computational aspects

This work presents an analysis of the wavelet-Galerkin method for one-dimensional elastoplastic-damage problems. Time-stepping algorithm for non-linear dynamics is presented. Numerical treatment of the constitutive models is developed by the use of return-mapping algorithm. For spacial discretization we can use wavelet-Galerkin method instead of standard finite element method. This approach allows to locate singularities. The discrete formulation developed can be applied to the simulation of one-dimensional problems for elastic-plastic-damage models. (C) 2007 Elsevier Inc. All rights reserved.

HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

An Alternative Optical Method for Acoustic Resonance Detection in HID Lamps

Acoustic resonances are observed in high-pressure discharge lamps operated with ac input modulated power frequencies in the kilohertz range. This paper describes an optical resonance detection method for high-intensity discharge lamps using computer-controlled cameras and image processing software. Experimental results showing acoustic resonances in high-pressure sodium lamps are presented.

Ultrasound, eddy current and magnetic Barkhausen noise as tools for sigma phase detection on a UNS S31803 duplex stainless steel

Sigma phase is a deleterious one which can be formed in duplex stainless steels during heat treatment or welding. Aiming to accompany this transformation, ferrite and sigma percentage and hardness were measured on samples of a UNS S31803 duplex stainless steel submitted to heat treatment. These results were compared to measurements obtained from ultrasound and eddy current techniques, i.e., velocity and impedance, respectively. Additionally, backscattered signals produced by wave propagation were acquired during ultrasonic inspection as well as magnetic Barkhausen noise during magnetic inspection. Both signal types were processed via a combination of detrended-fluctuation analysis (DFA) and principal component analysis (PCA). The techniques used were proven to be sensitive to changes in samples related to sigma phase formation due to heat treatment. Furthermore, there is an advantage using these methods since they are nondestructive. (C) 2010 Elsevier B.V. All rights reserved.

NDT flaw mapping of steel surfaces by continuous magnetic Barkhausen noise: Volumetric flaw detection case

This paper reports the use of a non-destructive, continuous magnetic Barkhausen noise (CMBN) technique to investigate the size and thickness of volumetric defects, in a 1070 steel. The magnetic behavior of the used probe was analyzed by numerical simulation, using the finite element method (FEM). Results indicated that the presence of a ferrite coil core in the probe favors MBN emissions. The samples were scanned with different speeds and probe configurations to determine the effect of the flaw on the CMBN signal amplitude. A moving smooth window, based on a second-order statistical moment, was used for analyzing the time signal. The results show the technique`s good repeatability, and high capacity for detection of this type of defect. (C) 2009 Elsevier Ltd. All rights reserved.