GC analysis of organotin compounds using pulsed flame photometric detection and conventional flame photometric detection

Organotin compounds, largely used as biocides in antifouling paints, are among the most toxic materials introduced into the aquatic environment. Sensitive analytical methods are thus required to characterize their occurrence in environmental and biological matrices. The comparison between two different photometric detectors in terms of analytical performance was carried out for the analysis of organotin compounds. A flame photometric detector (FPD) and a pulsed flame photometric detector (PFPD) were optimized. Their respective sensitivity, linearity range and selectivity were evaluated. Limits of detection obtained for a tributyltin compound (TBT) were 5.0 and 0.9 pg (as Sn) for the FPD and PFPD, respectively, using a 390 nm filter. The PFPD showed higher selectivity, besides reduced gas consumption in the flame, and is very attractive for organotin compound speciation in complex environmental matrices.

Epstein-Barr Virus (EBV) detection and typing by PCR: a contribution to diagnostic screening of EBV-positive Burkitt's lymphoma

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Detection and quantification of antibodies to Newcastle disease virus in ostrich and rhea sera using a liquid phase blocking enzyme-linked immunosorbent assay

A liquid phase blocking ELISA (LPB-ELISA) was adapted for the detection and quantification of antibodies to Newcastle disease virus. Sera from vaccinated and unvaccinated commercial flocks of ostriches (Struthio camelus) and rheas (Rhea americana) were tested. The purified and nonpurified virus used as the antigen and the capture and detector antibodies were prepared and standardized for this purpose. The hemagglutination-inhibition (HI) test was regarded as the reference method, the cutoff point for the LPB-ELISA was determined by a two-graph receiver operating characteristic analysis. The LPB-ELISA titers regressed significantly (P < 0.0001) on the HI titers with a high correlation coefficient (r = 0.875). The two tests showed good agreement ( = 0.82; P < 0.0001), relative sensitivity (90.91%) and specificity (91.18%), and accuracy (91.02%), suggesting that they are interchangeable.

Detection and localization of small nuclear ribonucleoproteins (snRNPs) in trypanosomatids using anti-m(3)G antibodies

This work reports for the first time the identification and immunolocalization, by confocal and conventional indirect immunofluorescence, of m(3)G epitopes present in ribonucleoproteins of the following trypanosomatids: Trypanosoma cruzi epimastigotes of three different strains, Blastocrithidia ssp., and Leishmania major promastigotes. The identity of these epitopes and hence the specificity of the anti-m(3)G monoclonal antibody were ascertained through competition reaction with 7-methylguanosine that blocks the Ig binding sites, abolishing the fluorescence in all the parasites tested and showing a specific perinuclear localization of the snRNPs, which suggests their nuclear reimport in the parasites. Using an immunoprecipitation technique, it was also possible to confirm the presence of the trimethylguanosine epitopes in trypanosomatids.

Detection and neutralization of venom by ovine antiserum in experimental envenoming by Bothrops jararaca

In this study we optimized an enzyme-linked immunosorbent assay (ELISA) to evaluate bothropic venom levels in biological samples. These samples were obtained by two distinct protocols. In the first one, Swiss mice were injected with 1 LD 50 of Bothrops jararaca (B. jararaca) venom and 15 minutes later, animals were treated with ovine antibothropic serum. Blood and spleen homogenate samples were obtained 6 hours after antiserum therapy. Ovine antibothropic serum significantly neutralized venom levels in serum and spleen. In the second protocol, BALB/c mice were injected with 1 LD 50 of bothropic venom by either intraperitoneal (IP) or intradermal (ID) route and venom levels were evaluated 1, 3 and 6 hours after, in blood, spleen homogenates and urine. Serum and splenic venom levels were significantly higher in animals envenomed by IP route comparing with animals envenomed by ID route. Higher venom levels were also detected in urine samples from animals envenomed by IP route. However, these differences were not statistically significant. These results demonstrated that the optimized ELISA was adequate to quantify venom levels in different biological samples. This assay could, therefore, substitute the in vivo neutralizing assay and also be useful to evaluate the severity of human and experimental envenomations.

Microcalcification enhancement and classification on mammograms using the wavelet transform

This paper presents a method to enhance microcalcifications and classify their borders by applying the wavelet transform. Decomposing an image and removing its low frequency sub-band the microcalcifications are enhanced. Analyzing the effects of perturbations on high frequency subband it's possible to classify its borders as smooth, rugged or undefined. Results show a false positive reduction of 69.27% using a region growing algorithm. © 2008 IEEE.

Delay time detection and accommodation for a networked DC motor control

This paper presents a control method that is effective to reduce the degenerative effects of delay time caused by a treacherous network. In present application a controlled DC motor is part of an inverted pendulum and provides the equilibrium of this system. The control of DC motor is accomplished at the distance through a treacherous network, which causes delay time in the control signal. A predictive technique is used so that it turns the system free of delay. A robust digital sliding mode controller is proposed to control the free-delay system. Due to the random conditions of the network operation, a delay time detection and accommodation strategy is also proposed. A computer simulation is shown to illustrate the design procedures and the effectiveness of the proposed method. © 2011 IEEE.

Dynamic voltage restorer development and testing

The growing use of sensitive loads in the electric power system, especially in industrial applications, increases voltage sags related production losses considerably, stimulating a demand for power electronics' based solutions to mitigate the effects of such problems. This paper shows the implementation and some industrial certification tests of a power equipment prototype designed to correct sags and swells, a dynamic voltage restorer, which is one of the many possible solutions for voltage sags and swells problems Experimental results of a 75kVA prototype are shown both in laboratory and full load conditions, in a certification institution (IEE-USP). © 2011 IEEE.

QK-Means: A clustering technique based on community detection and K-Means for deployment of cluster head nodes

Wireless Sensor Networks (WSN) are a special kind of ad-hoc networks that is usually deployed in a monitoring field in order to detect some physical phenomenon. Due to the low dependability of individual nodes, small radio coverage and large areas to be monitored, the organization of nodes in small clusters is generally used. Moreover, a large number of WSN nodes is usually deployed in the monitoring area to increase WSN dependability. Therefore, the best cluster head positioning is a desirable characteristic in a WSN. In this paper, we propose a hybrid clustering algorithm based on community detection in complex networks and traditional K-means clustering technique: the QK-Means algorithm. Simulation results show that QK-Means detect communities and sub-communities thus lost message rate is decreased and WSN coverage is increased. © 2012 IEEE.

Technique to combine images produced by different propagation modes of guided waves for damage detection and contrast improvement in plate-like structures

This paper describes an image compounding technique based on the use of different apodization functions, the evaluation of the signals phases and information from the interaction of different propagation modes of Lamb waves with defects for enhanced damage detection, resolution and contrast. A 16 elements linear array is attached to a 1 mm thickness isotropic aluminum plate with artificial defects. The array can excite the fundamental A0 and S0 modes at the frequencies of 100 kHz and 360 kHz, respectively. For each mode two synthetic aperture (SA) images with uniform and Blackman apodization and one image of Coherence Factor Map (CFM) are obtained. The specific interaction between each propagation mode and the defects and the characteristics of acoustic radiation patterns due to different apodization functions result in images with different resolution and contrast. From the phase information one of the SA images is selected at each pixel to compound the final image. The SA images are multiplied by the CFM image to improve contrast and for the dispersive A0 mode it is used a technique for dispersion compensation. There is a contrast improvement of 47.5 dB, reducing the dead zone and improving resolution and damage detection. © 2012 IEEE.

Automatic microstructural characterization and classification using artificial intelligence techniques on ultrasound signals

Secondary phases such as Laves and carbides are formed during the final solidification stages of nickel based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ″ and δ phases. This work presents a new application and evaluation of artificial intelligent techniques to classify (the background echo and backscattered) ultrasound signals in order to characterize the microstructure of a Ni-based alloy thermally aged at 650 and 950 °C for 10, 100 and 200 h. The background echo and backscattered ultrasound signals were acquired using transducers with frequencies of 4 and 5 MHz. Thus with the use of features extraction techniques, i.e.; detrended fluctuation analysis and the Hurst method, the accuracy and speed in the classification of the secondary phases from ultrasound signals could be studied. The classifiers under study were the recent optimum-path forest (OPF) and the more traditional support vector machines and Bayesian. The experimental results revealed that the OPF classifier was the fastest and most reliable. In addition, the OPF classifier revealed to be a valid and adequate tool for microstructure characterization through ultrasound signals classification due to its speed, sensitivity, accuracy and reliability. © 2013 Elsevier B.V. All rights reserved.