882 resultados para Automated isolation
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Morphological descriptors are practical and essential biomarkers for diagnosis andtreatment selection for intracranial aneurysm management according to the current guidelinesin use. Nevertheless, relatively little work has been dedicated to improve the three-dimensionalquanti cation of aneurysmal morphology, automate the analysis, and hence reduce the inherentintra- and inter-observer variability of manual analysis. In this paper we propose a methodologyfor the automated isolation and morphological quanti cation of saccular intracranial aneurysmsbased on a 3D representation of the vascular anatomy.
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This paper focuses on improving computer network management by the adoption of artificial intelligence techniques. A logical inference system has being devised to enable automated isolation, diagnosis, and even repair of network problems, thus enhancing the reliability, performance, and security of networks. We propose a distributed multi-agent architecture for network management, where a logical reasoner acts as an external managing entity capable of directing, coordinating, and stimulating actions in an active management architecture. The active networks technology represents the lower level layer which makes possible the deployment of code which implement teleo-reactive agents, distributed across the whole network. We adopt the Situation Calculus to define a network model and the Reactive Golog language to implement the logical reasoner. An active network management architecture is used by the reasoner to inject and execute operational tasks in the network. The integrated system collects the advantages coming from logical reasoning and network programmability, and provides a powerful system capable of performing high-level management tasks in order to deal with network fault.
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Activated sludge models are used extensively in the study of wastewater treatment processes. While various commercial implementations of these models are available, there are many people who need to code models themselves using the simulation packages available to them, Quality assurance of such models is difficult. While benchmarking problems have been developed and are available, the comparison of simulation data with that of commercial models leads only to the detection, not the isolation of errors. To identify the errors in the code is time-consuming. In this paper, we address the problem by developing a systematic and largely automated approach to the isolation of coding errors. There are three steps: firstly, possible errors are classified according to their place in the model structure and a feature matrix is established for each class of errors. Secondly, an observer is designed to generate residuals, such that each class of errors imposes a subspace, spanned by its feature matrix, on the residuals. Finally. localising the residuals in a subspace isolates coding errors. The algorithm proved capable of rapidly and reliably isolating a variety of single and simultaneous errors in a case study using the ASM 1 activated sludge model. In this paper a newly coded model was verified against a known implementation. The method is also applicable to simultaneous verification of any two independent implementations, hence is useful in commercial model development.
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The fundamental role of dendritic cells (DC in initiating and directing the primary immune response is well established. Furthermore, it is now accepted that DC may be useful in new vaccination strategies for preventing certain malignant and infectious diseases. As blood DC (BDC physiology differs from that of the DC homologues generated in vitro from monocyte precursors, it is becoming more relevant to consider BDC for therapeutic interventions. Until recently, protocols for the isolation of BDC were laborious and inefficient; therefore, their use for investigative cancer immunotherapy is not widespread. In this study, we carefully documented BDC counts, yields and subsets during apheresis (Cobe Spectra), the initial and essential procedure in creating a BDC isolation platform for cancer immunotherapy. We established that an automated software package (Version 6,0 AutoPBPC) provides an operator-independent reliable source of motionuclear cells (MNC for BDC preparation. Further, we observed that BDC might be recovered in high yields, often greater than 100% relative to the number of circulating BDC predicted by blood volume. An average of 66 million (range, 17-179) BDC per 10-1 procedure were obtained, largely satisfying the needs for immunization. Higher yields were possible on total processed blood volumes of 151. BDC were not activated by the isolation procedure and, more importantly, both BDC subsets (CD11c(+)CD123(low) and CD11c(-)CD123(high)) were equally represented. Finally, we established that the apheresis product could be used for antibody-based BDC immunoselection and demonstrated that fully functional BDC can be obtained by this procedure. (C) 2002 Published by Elsevier Science B.V.
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The quality of sample inoculation is critical for achieving an optimal yield of discrete colonies in both monomicrobial and polymicrobial samples to perform identification and antibiotic susceptibility testing. Consequently, we compared the performance between the InoqulA (BD Kiestra), the WASP (Copan), and manual inoculation methods. Defined mono- and polymicrobial samples of 4 bacterial species and cloudy urine specimens were inoculated on chromogenic agar by the InoqulA, the WASP, and manual methods. Images taken with ImagA (BD Kiestra) were analyzed with the VisionLab version 3.43 image analysis software to assess the quality of growth and to prevent subjective interpretation of the data. A 3- to 10-fold higher yield of discrete colonies was observed following automated inoculation with both the InoqulA and WASP systems than that with manual inoculation. The difference in performance between automated and manual inoculation was mainly observed at concentrations of >10(6) bacteria/ml. Inoculation with the InoqulA system allowed us to obtain significantly more discrete colonies than the WASP system at concentrations of >10(7) bacteria/ml. However, the level of difference observed was bacterial species dependent. Discrete colonies of bacteria present in 100- to 1,000-fold lower concentrations than the most concentrated populations in defined polymicrobial samples were not reproducibly recovered, even with the automated systems. The analysis of cloudy urine specimens showed that InoqulA inoculation provided a statistically significantly higher number of discrete colonies than that with WASP and manual inoculation. Consequently, the automated InoqulA inoculation greatly decreased the requirement for bacterial subculture and thus resulted in a significant reduction in the time to results, laboratory workload, and laboratory costs.
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This paper describes the development and evaluation of a sequential injection method to automate the determination of methyl parathion by square wave adsorptive cathodic stripping voltammetry exploiting the concept of monosegmented flow analysis to perform in-line sample conditioning and standard addition. Accumulation and stripping steps are made in the sample medium conditioned with 40 mmol L-1 Britton-Robinson buffer (pH 10) in 0.25 mol L-1 NaNO3. The homogenized mixture is injected at a flow rate of 10 mu Ls(-1) toward the flow cell, which is adapted to the capillary of a hanging drop mercury electrode. After a suitable deposition time, the flow is stopped and the potential is scanned from -0.3 to -1.0 V versus Ag/AgCl at frequency of 250 Hz and pulse height of 25 mV The linear dynamic range is observed for methyl parathion concentrations between 0.010 and 0.50 mgL(-1), with detection and quantification limits of 2 and 7 mu gL(-1), respectively. The sampling throughput is 25 h(-1) if the in line standard addition and sample conditioning protocols are followed, but this frequency can be increased up to 61 h(-1) if the sample is conditioned off-line and quantified using an external calibration curve. The method was applied for determination of methyl parathion in spiked water samples and the accuracy was evaluated either by comparison to high performance liquid chromatography with UV detection, or by the recovery percentages. Although no evidences of statistically significant differences were observed between the expected and obtained concentrations, because of the susceptibility of the method to interference by other pesticides (e.g., parathion, dichlorvos) and natural organic matter (e.g., fulvic and humic acids), isolation of the analyte may be required when more complex sample matrices are encountered. (C) 2007 Elsevier B.V. All rights reserved.
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The study evaluated sources of within- and between-subject variability in standard white-on-white (W-W) perimetry and short-wavelength automated perimetry (SWAP). The Influence of staircase strategy on the fatigue effect in W-W perimetry was investigated for a 4 dB single step, single reversal strategy; a variable step size, single reversal dynamic strategy; and the standard 4-2 dB double reversal strategy. The fatigue effect increased as the duration of the examination Increased and was greatest in the second eye for all strategies. The fatigue effect was lowest for the 4dB strategy, which exhibited the shortest examination time and was greatest for the 4-2 dB strategy, which exhibited the longest examination time. Staircase efficiency was lowest for the 4 dB strategy and highest for the dynamic strategy which thus offers a reduced examination time and low inter-subject variability. The normal between-subject variability of SWAP was determined for the standard 4-2 dB double reversal strategy and the 3 dB single reversal FASTPAC strategy and compared to that of W-W perimetry, The decrease in sensitivity with Increase in age was greatest for SWAP. The between-subject variability of SWAP was greater than W-W perimetry. Correction for the Influence of ocular media absorption reduced the between-subject variability of SWAP, The FASTPAC strategy yielded the lowest between-subject variability In SWAP, but the greatest between-subject variability In WoW perimetry. The greater between-subject variability of SWAP has profound Implications for the delineation of visual field abnormality, The fatigue effect for the Full Threshold strategy in SWAP was evaluated with conventional opaque, and translucent occlusion of the fellow eye. SWAP exhibited a greater fatigue effect than W-W perimetry. Translucent occlusion reduced the between-subject variability of W-W perimetry but Increased the between-subject variability of SWAP. The elevation of sensitivity was greater with translucent occlusion which has implications for the statistical analysis of W-W perimetry and SWAP. The influence of age-related cataract extraction and IOL implantation upon the visual field derived by WoW perimetry and SWAP was determined. Cataract yielded a general reduction In sensitivity which was preferentially greater in SWAP, even after the correction of SWAP for the attenuation of the stimulus by the ocular media. There was no correlation between either backward or forward light scatter and the magnitude of the attenuation of W-W or SWAP sensitivity. The post-operative mean deviation in SWAP was positive and has ramifications for the statistical Interpretation of SWAP. Short-wavelength-sensitive pathway isolation was assessed as a function of stimulus eccentricity using the two-colour Increment threshold method. At least 15 dB of SWS pathway Isolation was achieved for 440 nm, 450 nm and 460 nm stimuli at a background luminance of 100 cdm-2, There was a slight decrease In SWS pathway Isolation for all stimulus wavelengths with increasing eccentricity which was not of clinical significance. Adopting a 450 nm stimulus may reduce between-subject variability In SWAP due to a reduction In ocular media absorption and macular pigment absorption.
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Many software engineers have found that it is difficult to understand, incorporate and use different formal models consistently in the process of software developments, especially for large and complex software systems. This is mainly due to the complex mathematical nature of the formal methods and the lack of tool support. It is highly desirable to have software models and their related software artefacts systematically connected and used collaboratively, rather than in isolation. The success of the Semantic Web, as the next generation of Web technology, can have profound impact on the environment for formal software development. It allows both the software engineers and machines to understand the content of formal models and supports more effective software design in terms of understanding, sharing and reusing in a distributed manner. To realise the full potential of the Semantic Web in formal software development, effectively creating proper semantic metadata for formal software models and their related software artefacts is crucial. This paper proposed a framework that allows users to interconnect the knowledge about formal software models and other related documents using the semantic technology. We first propose a methodology with tool support is proposed to automatically derive ontological metadata from formal software models and semantically describe them. We then develop a Semantic Web environment for representing and sharing formal Z/OZ models. A method with prototype tool is presented to enhance semantic query to software models and other artefacts. © 2014.
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This study tested whether myocardial extracellular volume (ECV) is increased in patients with hypertension and atrial fibrillation (AF) undergoing pulmonary vein isolation and whether there is an association between ECV and post-procedural recurrence of AF. Hypertension is associated with myocardial fibrosis, an increase in ECV, and AF. Data linking these findings are limited. T1 measurements pre-contrast and post-contrast in a cardiac magnetic resonance (CMR) study provide a method for quantification of ECV. Consecutive patients with hypertension and recurrent AF referred for pulmonary vein isolation underwent a contrast CMR study with measurement of ECV and were followed up prospectively for a median of 18 months. The endpoint of interest was late recurrence of AF. Patients had elevated left ventricular (LV) volumes, LV mass, left atrial volumes, and increased ECV (patients with AF, 0.34 ± 0.03; healthy control patients, 0.29 ± 0.03; p < 0.001). There were positive associations between ECV and left atrial volume (r = 0.46, p < 0.01) and LV mass and a negative association between ECV and diastolic function (early mitral annular relaxation [E'], r = -0.55, p < 0.001). In the best overall multivariable model, ECV was the strongest predictor of the primary outcome of recurrent AF (hazard ratio: 1.29; 95% confidence interval: 1.15 to 1.44; p < 0.0001) and the secondary composite outcome of recurrent AF, heart failure admission, and death (hazard ratio: 1.35; 95% confidence interval: 1.21 to 1.51; p < 0.0001). Each 10% increase in ECV was associated with a 29% increased risk of recurrent AF. In patients with AF and hypertension, expansion of ECV is associated with diastolic function and left atrial remodeling and is a strong independent predictor of recurrent AF post-pulmonary vein isolation.
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The aim of this study was to compare the performance of the following techniques on the isolation of volatiles of importance for the aroma/flavor of fresh cashew apple juice: dynamic headspace analysis using PorapakQ(®) as trap, solvent extraction with and without further concentration of the isolate, and solid-phase microextraction (fiber DVB/CAR/PDMS). A total of 181 compounds were identified, from which 44 were esters, 20 terpenes, 19 alcohols, 17 hydrocarbons, 15 ketones, 14 aldehydes, among others. Sensory evaluation of the gas chromatography effluents revealed esters (n = 24) and terpenes (n = 10) as the most important aroma compounds. The four techniques were efficient in isolating esters, a chemical class of high impact in the cashew aroma/flavor. However, the dynamic headspace methodology produced an isolate in which the analytes were in greater concentration, which facilitates their identification (gas chromatography-mass spectrometry) and sensory evaluation in the chromatographic effluents. Solvent extraction (dichloromethane) without further concentration of the isolate was the most efficient methodology for the isolation of terpenes. Because these two techniques also isolated in greater concentration the volatiles from other chemical classes important to the cashew aroma, such as aldehydes and alcohols, they were considered the most advantageous for the study of cashew aroma/flavor.
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PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.
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A wide variety of opportunistic pathogens has been detected in the tubing supplying water to odontological equipment, in special in the biofilm lining of these tubes. Among these pathogens, Pseudomonas aeruginosa, one of the leading causes of nosocomial infections, is frequently found in water lines supplying dental units. In the present work, 160 samples of water, and 200 fomite samples from forty dental units were collected in the city of Barretos, State of São Paulo, Brazil and evaluated between January and July, 2005. Seventy-six P. aeruginosa strains, isolated from the dental environment (5 strains) and water system (71 strains), were tested for susceptibility to six antimicrobial drugs most frequently used against P. aeruginosa infections. Susceptibility to ciprofloxacin, followed by meropenem was the predominant profile. The need for effective means of reducing the microbial burden within dental unit water lines is emphasized, and the risk of exposure and cross-infection in dental practice, in special when caused by opportunistic pathogens like P. aeruginosa, are highlighted.
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From January to December 2006, 92 Escherichia coli isolates from 25 diarrheic dogs were analyzed by screening for the presence of adhesin-encoding genes (pap, sfa, afa), hemolysin and aerobactin genes. Virulence gene frequencies detected in those isolates were: 12% pap, 1% sfa, 10% hemolysin and 6.5% aerobactin. Ten isolates were characterized as extraintestinal pathogenic E. coli (ExPEC) strains; all showed a multidrug resistance phenotype that may represent a reason for concern due the risk of dissemination of antimicrobial resistant genes to the microbiota of human beings.
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Flavobacterium columnare is the causative agent of columnaris disease in freshwater fish, implicated in skin and gill disease, often causing high mortality. The aim of this study was the isolation and characterization of Flavobacterium columnare in tropical fish in Brazil. Piracanjuba (Brycon orbignyanus), pacu (Piaractus mesopotamicus), tambaqui (Colossoma macropomum) and cascudo (Hypostomus plecostomus) were examined for external lesions showing signs of colunmaris disease such as greyish white spots, especially on the head, dorsal part and caudal fin of the fish. The sampling comprised 50 samples representing four different fish species selected for study. Samples for culture were obtained by skin and kidney scrapes with a sterile cotton swabs of columnaris disease fish and streaked onto Carlson and Pacha (1968) artificial culture medium (broth and solid) which were used for isolation. The strains in the liquid medium were Gram negative, long, filamentous, exhibited flexing movements (gliding motility), contained a large number of long slender bacteria and gathered into ‘columns'. Strains on the agar produced yellow-pale colonies, rather small, flat that had rhizoid edges. A total of four Flavobacterium columnare were isolated: 01 Brycon orbignyanus strain, 01 Piaractus mesopotamicus strain, 01 Colossoma macropomum strain, and 01 Hypostomus plecostomus strain. Biochemical characterization, with its absorption of Congo red dye, production of flexirubin-type pigments, H2S production and reduction of nitrates proved that the isolate could be classified as Flavobacterium columnare.