Revendo os códigos hamming e CRC para tratar com erros na transmissão de dados

This article has the purpose to review the main codes used to detect and correct errors in data communication specifically in the computer's network. The Hamming's code and the Ciclic Redundancy Code (CRC) are presented as the focus of this article as well as CRC hardware implementation. Each code is reviewed in details in order to fill the gaps in the literature and to make it accessible to the computer science and engineering students as well as to anyone who may be interested in learning the technique to treat error in data communication.

Search for the flavor-changing neutral current decay Bs 0 → μ+ μ- pp̄ Collisions at √s = 1.96 TeV with the DO Detector

We present the results of a search for the flavor-changing neutral current decay Bs 0 → μ+ μ-. using a data set with integrated luminosity of 240 pb-1 of pp̄ collisions at √s = 1.96 TeV collected with the D0 detector in run II of the Fermilab Tevatron collider. We find the upper limit on the branching fraction to be B(Bs 0 → μ+ π-) ≤ 5.0 × 10-7 at the 95% C.L. assuming no contributions from the decay Bd 0 → μ+ μ- in the signal region. This limit is the most stringent upper bound on the branching fraction Bs 0 → μ+ μ- to date. © 2005 The American Physical Society.

Development of a new clean methodology with ultrasound-assisted extraction for analysis of sodium in pet foods

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

High sensitivity fiber optic angular displacement sensor and its application for detection of ultrasound

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

First detection of the equine herpesvirus 1 neuropathogenic variant in Brazil

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

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.

Spectrophotometric Determination of Paracetamol in Pharmaceuticals Using Microwave-Assisted Hydrolysis and a Micellar Medium

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

Spectrophotometric determination of diclofenac in pharmaceutical preparations assisted by microwave oven

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

A fast microwave-assisted, acid-vapor, steam-cleaning procedure for autosampler cups

A new and fast procedure is proposed for cleaning autosampler cups using acid-vapor steam-cleaning with a miniaturized assembly in a microwave-heated sealed Teflon vessel. A glass cactus-shaped holder was made to support six polyethylene autosampler cups (volume, 2.0 mt) inside a 100 mt microwave vessel. Regent-grade nitric acid was added to the vessels, and the system was heated in a microwave oven for 5 min at 300 W. Chromium was determined by graphite-furnace atomic-absorption spectrophotometry. The blank values were lower with cleaned cups compared to untreated cups (i.e., as received from supplier). The quantification limits, estimated from detection limits established with Milli-Q water, were 0.66 and 0.95 mu g Cr L-1 for cleaned and untreated auto-sampler cups, respectively. (C) 1998 Elsevier B.V. B.V. All rights reserved.

PrimerSNP: a web tool for whole-genome selection of allele-specific and common primers of phylogenetically-related bacterial genomic sequences

Background: The increasing number of genomic sequences of bacteria makes it possible to select unique SNPs of a particular strain/species at the whole genome level and thus design specific primers based on the SNPs. The high similarity of genomic sequences among phylogenetically-related bacteria requires the identification of the few loci in the genome that can serve as unique markers for strain differentiation. PrimerSNP attempts to identify reliable strain-specific markers, on which specific primers are designed for pathogen detection purpose.Results: PrimerSNP is an online tool to design primers based on strain specific SNPs for multiple strains/species of microorganisms at the whole genome level. The allele-specific primers could distinguish query sequences of one strain from other homologous sequences by standard PCR reaction. Additionally, PrimerSNP provides a feature for designing common primers that can amplify all the homologous sequences of multiple strains/species of microorganisms. PrimerSNP is freely available at http://cropdisease.ars.usda.gov/similar to primer.Conclusion: PrimerSNP is a high-throughput specific primer generation tool for the differentiation of phylogenetically-related strains/species. Experimental validation showed that this software had a successful prediction rate of 80.4 - 100% for strain specific primer design.

Use of the Normalized Absorbance Ratio as an Internal Standardization Approach To Minimize Measurement Error in Enzyme-Linked Immunosorbent Assays for Diagnosis of Human Papillomavirus Infection

The serological detection of antibodies against human papillomavirus (HPV) antigens is a useful tool to determine exposure to genital HPV infection and in predicting the risk of infection persistence and associated lesions. Enzyme-linked immunosorbent assays (ELISAs) are commonly used for seroepidemiological studies of HPV infection but are not standardized. Intra-and interassay performance variation is difficult to control, especially in cohort studies that require the testing of specimens over extended periods. We propose the use of normalized absorbance ratios (NARs) as a standardization procedure to control for such variations and minimize measurement error. We compared NAR and ELISA optical density (OD) values for the strength of the correlation between serological results for paired visits 4 months apart and HPV-16 DNA positivity in cervical specimens from a cohort investigation of 2,048 women tested with an ELISA using HPV-16 virus-like particles. NARs were calculated by dividing the mean blank-subtracted (net) ODs by the equivalent values of a control serum pool included in the same plate in triplicate, using different dilutions. Stronger correlations were observed with NAR values than with net ODs at every dilution, with an overall reduction in nonexplained regression variability of 39%. Using logistic regression, the ranges of odds ratios of HPV-16 DNA positivity contrasting upper and lower quintiles at different dilutions and their averages were 4.73 to 5.47 for NARs and 2.78 to 3.28 for net ODs, with corresponding significant improvements in seroreactivity-risk trends across quintiles when NARs were used. The NAR standardization is a simple procedure to reduce measurement error in seroepidemiological studies of HPV infection.

Diagnostic agreement of conventional and inverted scanned panoramic radiographs in the detection of the mandibular canal and the mental foramen.

The aim of this study was to evaluate the diagnostic agreement of conventional panoramic radiographs and their inverted scanned images in the detection of the mandibular canal and mental foramen. A total of 77 panoramic radiographs obtained from the files of totally edentulous patients were used. Digitization was done by means of a scanner with brightness and contrast adjustment, as well as image inversion. The extension of mandibular canal was divided into anterior, middle, and posterior regions, and the presence of a radiopaque line that characterized the mandibular canal was classified according to a 5-point confidence scale. The mental foramen was classified in 4 types: continuous, separated, diffuse, and unidentified. Both conventional and inverted scanned panoramic radiographs were evaluated by 3 calibrated implantologists at 2 distinct moments with a minimum interval of 10 days between them. Intraexaminer agreement was evaluated by Kappa statistics by point and by 95% confidence interval. Because the intraexaminer level of agreement was low, interexaminer agreements could not be carried out. The results showed a substantial (in 2 situations), moderate (in 16 situations), and fair (in 18 situations) intraexaminer agreement for mandibular canal and a substantial (in 1 situation), fair (in 1 situation), and moderate (in 10 situations) intraeaminer agreement for mental foramen. There were no statistically significant differences in most instances. In conclusion, the diagnostic agreement of conventional and inverted scanned panoramic radiographs for detection of mandibular canal and mental foramen was low.

Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.

Fuzzy community structure detection by particle competition and cooperation

Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.

Damage detection in nonlinear structures using discrete-time volterra series

Structural damage identification is basically a nonlinear phenomenon; however, nonlinear procedures are not used currently in practical applications due to the complexity and difficulty for implementation of such techniques. Therefore, the development of techniques that consider the nonlinear behavior of structures for damage detection is a research of major importance since nonlinear dynamical effects can be erroneously treated as damage in the structure by classical metrics. This paper proposes the discrete-time Volterra series for modeling the nonlinear convolution between the input and output signals in a benchmark nonlinear system. The prediction error of the model in an unknown structural condition is compared with the values of the reference structure in healthy condition for evaluating the method of damage detection. Since the Volterra series separate the response of the system in linear and nonlinear contributions, these indexes are used to show the importance of considering the nonlinear behavior of the structure. The paper concludes pointing out the main advantages and drawbacks of this damage detection methodology. © (2013) Trans Tech Publications.