Biomimetic biosensor based on lipidic layers containing tyrosinase and lutetium bisphthalocyanine for the detection of antioxidants

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Structural damage detection by fuzzy clustering

The development of strategies for structural health monitoring (SHM) has become increasingly important because of the necessity of preventing undesirable damage. This paper describes an approach to this problem using vibration data. It involves a three-stage process: reduction of the time-series data using principle component analysis (PCA), the development of a data-based model using an auto-regressive moving average (ARMA) model using data from an undamaged structure, and the classification of whether or not the structure is damaged using a fuzzy clustering approach. The approach is applied to data from a benchmark structure from Los Alamos National Laboratory, USA. Two fuzzy clustering algorithms are compared: fuzzy c-means (FCM) and Gustafson-Kessel (GK) algorithms. It is shown that while both fuzzy clustering algorithms are effective, the GK algorithm marginally outperforms the FCM algorithm. (C) 2008 Elsevier Ltd. All rights reserved.

Edge detection and noise removal by use of a partial differential equation with automatic selection of parameters

This work deals with noise removal by the use of an edge preserving method whose parameters are automatically estimated, for any application, by simply providing information about the standard deviation noise level we wish to eliminate. The desired noiseless image u(x), in a Partial Differential Equation based model, can be viewed as the solution of an evolutionary differential equation u t(x) = F(u xx, u x, u, x, t) which means that the true solution will be reached when t ® ¥. In practical applications we should stop the time ''t'' at some moment during this evolutionary process. This work presents a sufficient condition, related to time t and to the standard deviation s of the noise we desire to remove, which gives a constant T such that u(x, T) is a good approximation of u(x). The approach here focused on edge preservation during the noise elimination process as its main characteristic. The balance between edge points and interior points is carried out by a function g which depends on the initial noisy image u(x, t0), the standard deviation of the noise we want to eliminate and a constant k. The k parameter estimation is also presented in this work therefore making, the proposed model automatic. The model's feasibility and the choice of the optimal time scale is evident through out the various experimental results.

Electrochemical genosensors for the detection of Bonamia parasite. Selection of single strand-DNA (ssDNA) probes by simulation of the secondary structure folding

A post-PCR nucleic acid work by comparing experimental data, from electrochemical genosensors, and bioinformatics data, derived from the simulation of the secondary structure folding and prediction of hybridisation reaction, was carried out in order to rationalize the selection of ssDNA probes for the detection of two Bonamia species, B. exitiosa and B. ostreae, parasites of Ostrea edulis.Six ssDNA probes (from 11 to 25 bases in length, 2 thiolated and 4 biotinylated) were selected within different regions of B. ostreae and B. exitiosa PCR amplicons (300 and 304 bases, respectively) with the aim to discriminate between these parasite species. ssDNA amplicons and probes were analyzed separately using the "Mfold Web Server" simulating the secondary structure folding behaviour. The hybridisation of amplicon-probe was predicted by means of "Dinamelt Web Server". The results were evaluated considering the number of hydrogen bonds broken and formed in the simulated folding and hybridisation process, variance in gaps for each sequence and number of available bases. In the experimental part, thermally denatured PCR products were captured at the sensor interface via sandwich hybridisation with surface-tethered probes (thiolated probes) and biotinylated signalling probes. A convergence between analytical signals and simulated results was observed, indicating the possibility to use bioinformatic data for ssDNA probes selection to be incorporated in genosensors. (C) 2011 Elsevier B.V. All rights reserved.

Diclofenac Abatement using Modified Solar Photo-Fenton Process with Ammonium Iron(III) Citrate

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development of an enzyme-linked immunosorbent assay for detection of IgM antibodies to Babesia bigemina in cattle

A crude antigenic preparation of Babesia bigemina was used to develop an ELISA for the detection of IgM antibodies. Optimal dilutions of the antigen, using positive and negative reference sera, were determined by checkerboard titrations. Negative sera from cattle imported from tick-free areas, serum samples collected from infected B. bigemina cattle were used to validate the test. The specificity was 94% and sensitivity of the Elisa 87.5%. Sera from 385 cattle deriving from areas free from tick-borne diseases, which were submitted to a preimmunization process, were screened by this technique. The Elisa detected seroconversion on the 14th day post-inoculation in animals either infested with Boophilus microplus ticks (infected with B. bigemina), or inoculated with B. bigemina infected blood. Antibody titers decreased after day 33; however, all animals remained positive until the end of the experiment (124 days). The ELISA described may prove to be an appropriate serological test for the detection of IgM antibodies against B. bigemina.

Well-conditioned robust observer for detection of family systems components

A new concept of fault detection and isolation using robust observation for systems with random noises is presented. The method selects the parameters from components that may fault during the process and constructs well conditioned robust observers, considering sensors faults. To isolate component failures via robust observation, a bank of detection observers is constructed, where each observer is only sensitive to one specified component failure while robust to all other component failures.

An enzyme-linked immunosorbent assay (ELISA) for detection of antibodies against Toxocara vitulorum in water buffaloes

Toxocara vitulorum, a parasite of the small intestine of cattle and water buffaloes, is mainly acquired by calves via the colostrum/milk from infected cows. To understand the development of immune responses in calves, antibody levels to a soluble extract antigen (Ex) from T. vitulorum infective larvae were measured by an indirect ELISA with sera of 15 buffalo calves, which were sampled every 15 days for the first 180 days after birth and 9 buffalo cows during the perinatal period. From all serum samples examined during the first 180 days, antibody level was lowest and highest in calves at 1 day of age before and after suckling colostrum, respectively, suggesting that the origin of antibodies was the colostrum. Immediately after birth, antibody levels in suckled calves remained at high levels until day 15, began to decrease to lower levels between 15 and 30 days and remained relatively stable until 120 days. By comparing the immune responses of these animals with their parasitological status it was considered possible to determine if passively acquired or actively produced antibodies provided protection against the infection. High numbers of T. vitulorum eggs in the feces between 30 and 60 days indicated that passively acquired antibodies did not provide protection against the infection, at least during these first days, and the maximum fecal egg counts during 30-45 days were coincident with decreased antibody levels. Between 60 and 120 days, when serum antibodies were detected at reduced, but stable levels, adult nematodes were expelled from the intestines and no more T. vitulorum eggs were found, suggesting development of acquired resistance. However, the potential and functional protective role of the antibodies against T. vitulorum infection and the process of self-cure requires further investigation. (C) 2001 Elsevier B.V. B.V. All rights reserved.

Screening and confirmation of PAHs in vegetable oil samples by use of supercritical fluid extraction in conjunction with liquid chromatography and fluorimetric detection

A fast, simple, non-destructive method for the direct screening of polycyclic aromatic hydrocarbons (PAHs) in vegetable oil samples is proposed. The method uses a supercritical fluid extraction (SFE) system coupled on-line with a fluorimetric detector to determine PAHs. This special assembly avoids the main problems encountered in the determination of PAHs in complex matrices such as vegetable oils. PAHs are selectively extracted by using silica gel in the thimble and cleaned up by passage through a C18 column. Interferences are preferentially retained by the silica gel during the SFE process while PAHs are adsorbed in the C18 column and the remainder of the matrix is sent to waste. Finally, the C18 column is purged to remove residual CO2 gas and adsorbed PAHs are recovered by desorption with a solvent. The extracts from positive samples are subsequently analyzed by liquid chromatography (LC) with fluorescence detection. The proposed method allows the confirmation of vegetable oil safety and hence provides a new tool for consumer protection. (C) 2004 Elsevier B.V. All rights reserved.

Detection of cracks in scratching tests in ceramic materials through acoustic emission

The mechanisms of material removal and the interactions among scratches performed in ceramic materials were investigated using acoustic emission signals, and scanning electron microscopy, in scratching experiments. Several testing conditions were used to produce different types of removing mechanism on a glass as well as on a polycrystalline alumina sample composed by heterogeneous grain size. It is known that the material removing process on a polycrystalline ceramic involves intergranular microfracture and grain dislodgement, unlike the chipping produced by the extension of lateral cracks in non-granular materials, such as glass. Distinct settings for velocities, loads, and two types of diamond indenter were tested. The material removal was carried out by three different methods of scratching: single passes, repeated overlapping passes, and parallel scratches. As a general result, there was a clear relationship between the acoustic emission signals and the damage intensity occurred in the material removal. More specifically, there were differences in the acoustic emission signal levels in the scratches made on the alumina and on the glass owing to the material removal mechanisms associated with the structure of these materials. A gradual increase in the acoustic emission levels was observed when the number of repeated passes was increased as a result of the damage accumulation process followed by severe material removal. It was also noticed that the acoustic emission signals were capable of reflecting the interactions between two parallel scratches.

Leak detection in petroleum pipelines using a fuzzy system

A methodology for pipeline leakage detection using a combination of clustering and classification tools for fault detection is presented here. A fuzzy system is used to classify the running mode and identify the operational and process transients. The relationship between these transients and the mass balance deviation are discussed. This strategy allows for better identification of the leakage because the thresholds are adjusted by the fuzzy system as a function of the running mode and the classified transient level. The fuzzy system is initially off-line trained with a modified data set including simulated leakages. The methodology is applied to a small-scale LPG pipeline monitoring case where portability, robustness and reliability are amongst the most important criteria for the detection system. The results are very encouraging with relatively low levels of false alarms, obtaining increased leakage detection with low computational costs. (c) 2005 Elsevier B.V. All rights reserved.

Surface-enhanced resonance Raman scattering as an analytical tool for single molecule detection

A perylene derivative, n-(n-butyl)-n'-(4-aminobutyl) perylene-3,4,9,10-tetracarboxylic acid diimide (simplified as nBu-PTCD-(CH2)(4)-NH2) has been chosen as the target molecule for studies involving single molecule detection (SMD) using Raman scattering. The enhancement of the Raman signal is the result of the multiplicative effects of two phenomena, resonance Raman scattering (RRS) and surface-enhanced Raman scattering (SERS), which leads to the resulting surface-enhanced resonance Raman scattering (SERRS) process. The SERRS spectra from a single molecule have been collected using both silver and gold colloids. The SMD detection of the fundamental vibrational frequencies characteristic of nBu-PTCD-(CH2)(4)-NH2 is complemented with the detection of some overtones and combinations from ring stretching modes at the single molecule level. The background characterization of the ensemble vibrational spectroscopy of the target perylene and its SERRS is also presented, which includes the UV-vis absorption, experimental and calculated Raman scattering and infrared absorption, and molecular organization using reflection-absorption infrared spectroscopy (RAIRS).

Polysiloxane-poly(propylene oxide) hybrid discs as solid phase in anti-HCV detection using a recombinant core protein

In this work, siloxane-poly(propylene oxide) discs (PPO disc) prepared using the sol-gel process were used as solid phase in enzyme-linked immunosorbent assays (ELISA) for the detection of anti-hepatitis C virus (HCV) antibodies. The HCV RNA from serum (genotype 1b) was submitted to the RT-PCR technique and subsequent amplification of the HCV core 408 pb. This fragment was cloned into expression vector pET42a and expressed in Escherichia coli as recombinant protein with glutathione S-transferase (GST). Cell cultures were grown and induced having a final concentration of 0.4 x 10(-3) mol L-1 of IPTG. After induction, the cells were harvested and the soluble fraction was analyzed using polyacrilamide gel 15% showing a band with an approximate molecular weight of 44 kDa, the expected size for this GST-fused recombinant protein. The recombinant protein was purified and continued by immunological detection using HCV-positive serum and showed no cross-reactivity with positive samples for other infectious diseases. An ELISA was established using 1.25 ng of recombinant protein per PPO disc, a dilution of 1: 10,000 and 1:40 for a peroxidase conjugate and serum, respectively, and solutions of hydrogen peroxide and 3,3',5,5'-tetra-methylbenzidine in a ratio of 1: 1. The proposed methodology was compared with the ELISA conventional polystyrene-plate procedure and the performance of the PPO discs as a matrix for immunodetection gave an easy synthesis, good performance and reproducibility for commercial application. (c) 2007 Elsevier B.V. All rights reserved.

Well-conditioned robust observer for detection of faulty systems components

A new concept of fault detection and isolation using robust observation for systems with random noises is presented. The method selects the parameters from components that may fault during the process and constructs well conditioned robust observers, considering sensors faults. To isolate component failures via robust observation, a bank of detection observers is constructed, where each observer is only sensitive to one specified component failure while robust to all other component failures.

Automation in fault detection using neural network and model updating

In this article, an implementation of structural health monitoring process automation based on vibration measurements is proposed. The work presents an alternative approach which intent is to exploit the capability of model updating techniques associated to neural networks to be used in a process of automation of fault detection. The updating procedure supplies a reliable model which permits to simulate any damage condition in order to establish direct correlation between faults and deviation in the response of the model. The ability of the neural networks to recognize, at known signature, changes in the actual data of a model in real time are explored to investigate changes of the actual operation conditions of the system. The learning of the network is performed using a compressed spectrum signal created for each specific type of fault. Different fault conditions for a frame structure are evaluated using simulated data as well as measured experimental data.