54 resultados para Detecção de vírus


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Among placental mammals, primates are the only ones to present trichromatic color vision. However, the distribution of trichromacy among primates is not homogeneous: Old World primates shows an uniform trichromacy (with all individuals being trichromats) and New World primates exhibit a color vision polymorphism (with dichromatic males and dichromatic or trichromatic females). Visual ecology studies have investigated which selective pressures may have been responsible for the evolution of trichromacy in primates, diverging from the dichromat standard found in other mammals. Cues associated with foraging and the socio-reproductive status were analyzed, indicating a trichromatic advantage for the rapid detection of visually conspicuous objects against a green background. However, dichromats are characterized by an efficient capture of cryptic and camouflaged stimuli. These advantages regarding phenotype may be responsible for the maintenance of the visual polymorphism in New World primates and for the high incidence of color blindness in humans (standing around 8% in Caucasian men). An important factor that has not yet been experimentally taken into account is the predation risk and its effect on the evolution of trichromacy in primates. To answer this question, we prepared and edited pictures of animals with different coats: oncillas (Leopardus spp.), puma (Puma concolor) and ferret (Galictis cuja). The specimens were taxidermized and the photographs were taken in three different vegetation scenarios (dense forest, cerrado and grassland). The images of the predators were manipulated so that they fit into two categories of stimulus size (small or large). After color calibration and photo editing, these were presented to 40 humans (20 dichromats and 20 trichromats) by a computer program, which presented a set of four photos at a time (one picture containing the taxidermized animal amid the background vegetation and three depicting only the background vegetation) and recorded the response latency and success rate of the subjects. The results show a trichromatic advantage in detecting potential predators. The predator detection was influenced by the background, the predator species, the dimension of the stimulus and the observer s visual phenotype. As humans have a high rate of dyschromatopsias, when compared to wild Catarrhini or human tribal populations, it is possible that the increased rate of dichromats is a result of reduced pressure for rapid predator detection. Since our species came to live in more cohesive groups and resistant to attack by predators, with the advent of agriculture and the formation of villages, it is possible that the lower risk of predation has reduced the selection in favor of trichromats

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Soil contamination by pesticides is an environmental problem that needs to be monitored and avoided. However, the lack of fast, accurate and low cost analytical methods for discovering residual pesticide in complex matrices, such as soil, is a problem still unresolved. This problem needs to be solved before we are able to assess the quality of environmental samples. The intensive use of pesticides has increased since the 60s, because the dependence of their use, causing biological imbalances and promoting resistance and recurrence of high populations of pests and pathogens (upwelling). This has contributed to the appearance of new pests that were previously under natural control. To develop analytical methods that are able to quantify residues pesticide in complex environment. It is still a challenge for many laboratories. The integration of two analytical methods one ecotoxicological and another chemical demonstrates the potential for environmental analysis of methamidophos. The aim of this study was to evaluate an ecotoxicological method as "screening" analytical methamidophos in the soil and perform analytical confirmation in the samples of the concentration of the analyte by chemical method LC-MS/MS In this work we tested two soils: a clayey and sandy, both in contact with the kinetic methamidophos model followed pseudo-second order. The clay soil showed higher absorption of methamidophos and followed the Freundlich model, while the sandy, the Langmuir model. The chemical method was validated LC-MS/MS satisfactory, showing all parameters of linearity, range, precision, accuracy, and sensitivity adequate. In chronic ecotoxicological tests with C. dubia, the NOEC was 4.93 and 3.24 for ng L-1 of methamidophos to elutriate assays of sandy and clay soils, respectively. The method for ecotoxicological levels was more sensitive than LC-MS/MS detection of methamidophos, loamy and sandy soils. However, decreasing the concentration of the standard for analytical methamidophos and adjusting for the validation conditions chemical acquires a limit of quantification (LOQ) in ng L-1, consistent with the provisions of ecotoxicological test. The methods described should be used as an analytical tool for methamidophos in soil, and the ecotoxicological analysis can be used as a "screening" and LC-MS/MS as confirmatory analysis of the analyte molecule, confirming the objectives of this work

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Web services are software units that allow access to one or more resources, supporting the deployment of business processes in the Web. They use well-defined interfaces, using web standard protocols, making possible the communication between entities implemented on different platforms. Due to these features, Web services can be integrated as services compositions to form more robust loose coupling applications. Web services are subject to failures, unwanted situations that may compromise the business process partially or completely. Failures can occur both in the design of compositions as in the execution of compositions. As a result, it is essential to create mechanisms to make the implementation of service compositions more robust and to treat failures. Specifically, we propose the support for fault recovery in service compositions described in PEWS language and executed on PEWS-AM, an graph reduction machine. To support recovery failure on PEWS-AM, we extend the PEWS language specification and adapted the rules of translation and reduction of graphs for this machine. These contributions were made both in the model of abstract machine as at the implementation level

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Dengue is considered as the most important arthropod-borne viral disease throughout the world due to the high number of people at risk to be infected, mainly in tropical and subtropical regions of the planet. The etiologic agent is Dengue Virus (DENV), it is a single positive-stranded RNA virus of the family Flavivirus, genus Flaviviridae. Four serotypes are known, DENV-1, DENV-2, DENV-3 and DENV-4. One of the most important characteristic of these viruses is the genetic variability, which demands phylogenetic and evolutionary studies to understand key aspects like: epidemiology, virulence, migration patterns and antigenic characteristics. The objective of this study is the genetic characterization of dengue viruses circulating in the state of Rio Grande does Norte from January 2010 to December 2012. The complete E gene (1485 pb) of DENV1, 2 e 4 from Brazilian (Rio Grande do Norte) patients was sequenced. Phylogenetic analysis was performed using MEGA 5.2 software, Tamura-Nei model and Neighbor-Joining trees were inferred for the datasets. In Brazil, there is just one DENV-1 genotype (genotype V), one DENV-2 genotype (Asian/American) and two DENV-4 genotypes (genotypes I and II). Brazilian strains of DENV-1 are subdivided in two different lineages (BR-I and BR-II), the Brazilian strains of DENV-2 are subdivided in four lineages (BRI-IV) and genotype II of DENV-4 is subdivided in three Brazilian lineages (BRI-III). The viruses isolated in RN belong to lineage BR-II (DENV-1), BR-IV (DENV-2) and BR-III (DENV-4).The Caribbean and near Latin American countries are the main source of these viruses to Brazil. Amino acids substitutions were detected in three domains of E protein, this makes clear the necessity of studies that associate epidemiological and molecular data to better understand the effects of these mutations. This is the first study about genetic characterization and evolution of Dengue viruses in Rio Grande do Norte, Brazil

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In February 2011, the National Agency of Petroleum, Natural Gas and Biofuels (ANP) has published a new Technical Rules for Handling Land Pipeline Petroleum and Natural Gas Derivatives (RTDT). Among other things, the RTDT made compulsory the use of monitoring systems and leak detection in all onshore pipelines in the country. This document provides a study on the method for detection of transient pressure. The study was conducted on a industrial duct 16" diameter and 9.8 km long. The pipeline is fully pressurized and carries a multiphase mixture of crude oil, water and natural gas. For the study, was built an infrastructure for data acquisition and validation of detection algorithms. The system was designed with SCADA architecture. Piezoresistive sensors were installed at the ends of the duct and Digital Signal Processors (DSPs) were used for sampling, storage and processing of data. The study was based on simulations of leaks through valves and search for patterns that characterize the occurrence of such phenomena

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This work presents contributions in the detection and identication of faults in multilevel inverters through the study of the converters behavior under these operation conditions. Basically, the approached fault consists of an open-circuit in any switch of a three-level clamped diode inverter. The converter operation is characterized in the pre and post-fault states. A wave form behavior analysis of the pole voltage, phase current and dc-bus current is also done, which highlights characteristics that allow the detection of failure and, even, under favorable conditions, the identication of the faulty device. A compensation strategy of the approached fault (open-switch) is also investigated with the purpose of maintaining the driving system operational when a failure occurs. The proposed topology uses SCRs in parallel with the internal switches of the inverter, which allows, in some occasions, the full utilization of the dc-bus

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In this work, we propose a two-stage algorithm for real-time fault detection and identification of industrial plants. Our proposal is based on the analysis of selected features using recursive density estimation and a new evolving classifier algorithm. More specifically, the proposed approach for the detection stage is based on the concept of density in the data space, which is not the same as probability density function, but is a very useful measure for abnormality/outliers detection. This density can be expressed by a Cauchy function and can be calculated recursively, which makes it memory and computational power efficient and, therefore, suitable for on-line applications. The identification/diagnosis stage is based on a self-developing (evolving) fuzzy rule-based classifier system proposed in this work, called AutoClass. An important property of AutoClass is that it can start learning from scratch". Not only do the fuzzy rules not need to be prespecified, but neither do the number of classes for AutoClass (the number may grow, with new class labels being added by the on-line learning process), in a fully unsupervised manner. In the event that an initial rule base exists, AutoClass can evolve/develop it further based on the newly arrived faulty state data. In order to validate our proposal, we present experimental results from a level control didactic process, where control and error signals are used as features for the fault detection and identification systems, but the approach is generic and the number of features can be significant due to the computationally lean methodology, since covariance or more complex calculations, as well as storage of old data, are not required. The obtained results are significantly better than the traditional approaches used for comparison

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Objective to establish a methodology for the oil spill monitoring on the sea surface, located at the Submerged Exploration Area of the Polo Region of Guamaré, in the State of Rio Grande do Norte, using orbital images of Synthetic Aperture Radar (SAR integrated with meteoceanographycs products. This methodology was applied in the following stages: (1) the creation of a base map of the Exploration Area; (2) the processing of NOAA/AVHRR and ERS-2 images for generation of meteoceanographycs products; (3) the processing of RADARSAT-1 images for monitoring of oil spills; (4) the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products; and (5) the structuring of a data base. The Integration of RADARSAT-1 image of the Potiguar Basin of day 21.05.99 with the base map of the Exploration Area of the Polo Region of Guamaré for the identification of the probable sources of the oil spots, was used successfully in the detention of the probable spot of oil detected next to the exit to the submarine emissary in the Exploration Area of the Polo Region of Guamaré. To support the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products, a methodology was developed for the classification of oil spills identified by RADARSAT-1 images. For this, the following algorithms of classification not supervised were tested: K-means, Fuzzy k-means and Isodata. These algorithms are part of the PCI Geomatics software, which was used for the filtering of RADARSAT-1 images. For validation of the results, the oil spills submitted to the unsupervised classification were compared to the results of the Semivariogram Textural Classifier (STC). The mentioned classifier was developed especially for oil spill classification purposes and requires PCI software for the whole processing of RADARSAT-1 images. After all, the results of the classifications were analyzed through Visual Analysis; Calculation of Proportionality of Largeness and Analysis Statistics. Amongst the three algorithms of classifications tested, it was noted that there were no significant alterations in relation to the spills classified with the STC, in all of the analyses taken into consideration. Therefore, considering all the procedures, it has been shown that the described methodology can be successfully applied using the unsupervised classifiers tested, resulting in a decrease of time in the identification and classification processing of oil spills, if compared with the utilization of the STC classifier

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This study includes the results of the analysis of areas susceptible to degradation by remote sensing in semi-arid region, which is a matter of concern and affects the whole population and the catalyst of this process occurs by the deforestation of the savanna and improper practices by the use of soil. The objective of this research is to use biophysical parameters of the MODIS / Terra and images TM/Landsat-5 to determine areas susceptible to degradation in semi-arid Paraiba. The study area is located in the central interior of Paraíba, in the sub-basin of the River Taperoá, with average annual rainfall below 400 mm and average annual temperature of 28 ° C. To draw up the map of vegetation were used TM/Landsat-5 images, specifically, the composition 5R4G3B colored, commonly used for mapping land use. This map was produced by unsupervised classification by maximum likelihood. The legend corresponds to the following targets: savanna vegetation sparse and dense, riparian vegetation and exposed soil. The biophysical parameters used in the MODIS were emissivity, albedo and vegetation index for NDVI (NDVI). The GIS computer programs used were Modis Reprojections Tools and System Information Processing Georeferenced (SPRING), which was set up and worked the bank of information from sensors MODIS and TM and ArcGIS software for making maps more customizable. Initially, we evaluated the behavior of the vegetation emissivity by adapting equation Bastiaanssen on NDVI for spatialize emissivity and observe changes during the year 2006. The albedo was used to view your percentage of increase in the periods December 2003 and 2004. The image sensor of Landsat TM were used for the month of December 2005, according to the availability of images and in periods of low emissivity. For these applications were made in language programs for GIS Algebraic Space (LEGAL), which is a routine programming SPRING, which allows you to perform various types of algebras of spatial data and maps. For the detection of areas susceptible to environmental degradation took into account the behavior of the emissivity of the savanna that showed seasonal coinciding with the rainy season, reaching a maximum emissivity in the months April to July and in the remaining months of a low emissivity . With the images of the albedo of December 2003 and 2004, it was verified the percentage increase, which allowed the generation of two distinct classes: areas with increased variation percentage of 1 to 11.6% and the percentage change in areas with less than 1 % albedo. It was then possible to generate the map of susceptibility to environmental degradation, with the intersection of the class of exposed soil with varying percentage of the albedo, resulting in classes susceptibility to environmental degradation