Determination of Oxalate in Grass by FIA with a Spectrophotometric Detection System Using a Two Enzyme Reactor

A new methodology for soluble oxalic acid determination in grass samples was developed using a two enzyme reactor in an FIA system. The reactor consisted of 3 U of oxalate oxidase and 100 U of peroxidase immobilized on Sorghum vulgare seeds activated with glutaraldehyde. The carbon dioxide was monitored spectrophotometrically, after reacting with an acid-base indicator (Bromocresol Purple) after it permeated through a PTFE membrane. A linear response range was observed between 0.25 and 1.00mmol l-1 of oxalic acid; the data was fit by the equation A=-0.8(±1.5)+ 57.2(±2.5)[oxalate], with a correlation coefficient of 0.9971 and a relative standard deviation of 2% for n=5. The variance for a 0.25 mmol l-1 oxalic acid standard solution was lower than 4% for 11 measurements. The FIA system allows analysis of 20 samples per hour without prior treatment. The proposed method showed a good correlation with that of the Sigma Kit.

Intrusion detection system using optimum-path forest

Intrusion detection systems that make use of artificial intelligence techniques in order to improve effectiveness have been actively pursued in the last decade. Neural networks and Support Vector Machines have been also extensively applied to this task. However, their complexity to learn new attacks has become very expensive, making them inviable for a real time retraining. In this research, we introduce a new pattern classifier named Optimum-Path Forest (OPF) to this task, which has demonstrated to be similar to the state-of-the-art pattern recognition techniques, but extremely more efficient for training patterns. Experiments on public datasets showed that OPF classifier may be a suitable tool to detect intrusions on computer networks, as well as allow the algorithm to learn new attacks faster than the other techniques. © 2011 IEEE.

A malware detection system inspired on the human immune system

Malicious programs (malware) can cause severe damage on computer systems and data. The mechanism that the human immune system uses to detect and protect from organisms that threaten the human body is efficient and can be adapted to detect malware attacks. In this paper we propose a system to perform malware distributed collection, analysis and detection, this last inspired by the human immune system. After collecting malware samples from Internet, they are dynamically analyzed so as to provide execution traces at the operating system level and network flows that are used to create a behavioral model and to generate a detection signature. Those signatures serve as input to a malware detector, acting as the antibodies in the antigen detection process. This allows us to understand the malware attack and aids in the infection removal procedures. © 2012 Springer-Verlag.

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.

An Optimum-Path Forest framework for intrusion detection in computer networks

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

Pyroelectric composite film for X-ray intensity detection

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

A novel in situ Polymerase chain reaction hybridisation assay for the direct detection of bovine herpesvirus type 5 in formalin-fixed, paraffin-embedded tissues

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

An attack signature model to computer security intrusion detection

Internal and external computer network attacks or security threats occur according to standards and follow a set of subsequent steps, allowing to establish profiles or patterns. This well-known behavior is the basis of signature analysis intrusion detection systems. This work presents a new attack signature model to be applied on network-based intrusion detection systems engines. The AISF (ACME! Intrusion Signature Format) model is built upon XML technology and works on intrusion signatures handling and analysis, from storage to manipulation. Using this new model, the process of storing and analyzing information about intrusion signatures for further use by an IDS become a less difficult and standardized process.

Effects of Protein A in Detection of Canine Distemper Virus through immunosensor construction

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

Application of fuzzy logic for the evaluation of livestock slaughtering

A lógica fuzzy admite infinitos valores lógicos intermediários entre o falso e o verdadeiro. Com esse princípio, foi elaborado neste trabalho um sistema baseado em regras fuzzy, que indicam o índice de massa corporal de animais ruminantes com objetivo de obter o melhor momento para o abate. O sistema fuzzy desenvolvido teve como entradas as variáveis massa e altura, e a saída um novo índice de massa corporal, denominado Índice de Massa Corporal Fuzzy (IMC Fuzzy), que poderá servir como um sistema de detecção do momento de abate de bovinos, comparando-os entre si através das variáveis linguísticas )Muito BaixaM, ,BaixaB, ,MédiaM, ,AltaA e Muito AltaM. Para a demonstração e aplicação da utilização deste sistema fuzzy, foi feita uma análise de 147 vacas da raça Nelore, determinando os valores do IMC Fuzzy para cada animal e indicando a situação de massa corpórea de todo o rebanho. A validação realizada do sistema foi baseado em uma análise estatística, utilizando o coeficiente de correlação de Pearson 0,923, representando alta correlação positiva e indicando que o método proposto está adequado. Desta forma, o presente método possibilita a avaliação do rebanho, comparando cada animal do rebanho com seus pares do grupo, fornecendo desta forma um método quantitativo de tomada de decisão para o pecuarista. Também é possível concluir que o presente trabalho estabeleceu um método computacional baseado na lógica fuzzy capaz de imitar parte do raciocínio humano e interpretar o índice de massa corporal de qualquer tipo de espécie bovina e em qualquer região do País.

Immunohistochemistry in diagnostic veterinary pathology: a critical review

A técnica de imuno-histoquímica é usada na rotina diagnóstica e na pesquisa em patologia humana desde 1970, porém seu uso na patologia veterinária é relativamente recente, principalmente com objetivo diagnóstico. A maior dificuldade no uso da imuno-histoquímica na patologia veterinária tem sido a falta de anticorpos específicos para os tecidos animais. Na falta de anticorpos específicos para as espécies domésticas, a patologia veterinária freqüentemente faz uso de anticorpos que apresentam reatividade cruzada entre antígenos humanos e animais. O objetivo deste trabalho foi testar a reatividade cruzada de diversos anticorpos feitos para uso humano em tecido parafinado de algumas espécies animais, utilizando-se dos novos métodos de recuperação antigênica e amplificação da reação imuno-histoquímica. No presente estudo foi possível confirmar a aplicabilidade de que muitos anticorpos produzidos para diagnóstico imuno-histoquímico em patologia humana podem ser utilizados em patologia veterinária. Novos estudos são necessários a fim de se ampliar a lista de aplicabilidade desses anticorpos em diferentes espécies animais, levando sempre em consideração as variações de clones, diluições, métodos de recuperação antigênica e de revelação.

Drug resistance in Mycobacterium tuberculosis clinical isolates from Brazil: Phenotypic and genotypic methods

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Studies of the Electrochemical Degradation of Acetaminophen Using a Real-Time Biomimetic Sensor

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

Quantitative real-time PCR identifies a critical region of deletion on 22q13 related to prognosis in oral cancer

Quantitative real time PCR was performed on genomic DNA from 40 primary oral carcinomas and the normal adjacent tissues. The target genes ECGFB, DIA1, BIK, and PDGFB and the microsatellite markers D22S274 and D22S277, mapped on 22q13, were selected according to our previous loss of heterozygosity findings in head and neck tumors. Quantitative PCR relies on the comparison of the amount of product generated from a target gene and that generated from a disomic reference gene (GAPDH-housekeeping gene). Reactions have been performed with normal control in triplicates, using the 7700 Sequence Detection System (PE Applied Biosystems). Losses in the sequences D22S274 (22q13.31) and in the DIA1 (22q13.2-13.31) gene were detected in 10 out of 40 cases (25%) each. Statistically significant correlations were observed for patients with relative copy number loss of the marker D22S274 and stages T3-T4 of disease (P=0.025), family history of cancer (P = 0.001), and death (P = 0.021). Relative copy number loss involving the DIA1 gene was correlated to family history of cancer (P<0.001), death (P=0.002), and consumption of alcohol (P=0.026). Log-rank test revealed a significant decrease in survival (P=0.0018) for patients with DIA1 gene loss. Relative copy number losses detected in these sequences may be related to disease progression and a worse prognosis in patients with oral cancer.

Performance study of the CMS barrel resistive plate chambers with cosmic rays

In October and November 2008, the CMS collaboration conducted a programme of cosmic ray data taking, which has recorded about 270 million events. The Resistive Plate Chamber system, which is part of the CMS muon detection system, was successfully operated in the full barrel. More than 98% of the channels were operational during the exercise with typical detection efficiency of 90%. In this paper, the performance of the detector during these dedicated runs is reported. © 2010 IOP Publishing Ltd and SISSA.