978 resultados para Antigen-Antibody Complex -- analysis
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This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.
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A copper(II) chiral aza-bis(oxazoline) homogeneous catalyst (CuazaBox) was anchored onto the external surface of MCM-22 and ITQ-2 structures, as well as encapsulated into hierarchical MCM-22. The transition metal complex loading onto the porous solids was determined by ICP-AES and the materials were also characterized by elemental analysis (C, N, H, S), FTIR, XPS, TG and low temperature N-2 adsorption isotherms. The materials were tested as heterogeneous catalysts in the benchmark reaction of cyclopropanation of styrene to check the effect of the immobilization procedure on the catalytic parameters, as well as on their reutilization in several catalytic cycles. Catalyst CuazaBox anchored onto the external surface of MCM-22 and ITQ-2 materials were more active and enantioselective in the cyclopropanation of styrene than the corresponding homogeneous phase reaction run under similar experimental conditions. This is due to the propylation of the acidic aza-Box nitrogen. HMCM-22 was nevertheless the best heterogeneous catalyst. Encapsulation of CuazaBox on post-synthesis modified MCM-22 materials led to low activities and enantioselectivities. But reversal on the stereochemical course of the reaction was observed, probably due to confinement effect. (C) 2013 Elsevier Inc. All rights reserved.
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We present the first version of a new tool to scan the parameter space of generic scalar potentials, SCANNERS (Coimbra et al., SCANNERS project., 2013). The main goal of SCANNERS is to help distinguish between different patterns of symmetry breaking for each scalar potential. In this work we use it to investigate the possibility of excluding regions of the phase diagram of several versions of a complex singlet extension of the Standard Model, with future LHC results. We find that if another scalar is found, one can exclude a phase with a dark matter candidate in definite regions of the parameter space, while predicting whether a third scalar to be found must be lighter or heavier. The first version of the code is publicly available and contains various generic core routines for tree level vacuum stability analysis, as well as implementations of collider bounds, dark matter constraints, electroweak precision constraints and tree level unitarity.
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International Scientific Forum, ISF 2013, ISF 2013, 12-14 December 2013, Tirana.
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3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.
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The mechanisms of speech production are complex and have been raising attention from researchers of both medical and computer vision fields. In the speech production mechanism, the articulator’s study is a complex issue, since they have a high level of freedom along this process, namely the tongue, which instigates a problem in its control and observation. In this work it is automatically characterized the tongues shape during the articulation of the oral vowels of Portuguese European by using statistical modeling on MR-images. A point distribution model is built from a set of images collected during artificially sustained articulations of Portuguese European sounds, which can extract the main characteristics of the motion of the tongue. The model built in this work allows under standing more clearly the dynamic speech events involved during sustained articulations. The tongue shape model built can also be useful for speech rehabilitation purposes, specifically to recognize the compensatory movements of the articulators during speech production.
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Growing concern about the contamination of wastewaters by antibiotics demands fast but sensitive analytical methodologies, for the screening of a large number of samples. The purpose of this work was to develop a simple methodology, using direct injection of the samples, by HPLC with diode array detection (DAD), for a multiresidue analysis of five antibiotics of different classes. Wastewater from an urban water treatment plant was selected as a model to study possible coelution of interfering compounds. The linearity interval ranged from 40 to 400 µg/L for amoxicillin (Amox), metronidazole (Metro), cefazolin (Cefa), and chloramphenicol (Chloram) and from 20 to 200 µg/L for sulfamethoxazole (Sulfa), with LODs lower than 14 µg/L. Repeatability, expressed by the CV of six repeated injections, ranged from 1 to 8%, while the intermediate precision varied between 2 and 11%. The recovery ranged from 90 to 109%. This method enables the fast screening of a large number of samples, with an expanded uncertainty in the 1–22% range. The advantage of the proposed method is to significantly reduce the number of samples to be analyzed by more complex methods.
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Aiming the establishment of simple and accurate readings of citric acid (CA) in complex samples, citrate (CIT) selective electrodes with tubular configuration and polymeric membranes plus a quaternary ammonium ion exchanger were constructed. Several selective membranes were prepared for this purpose, having distinct mediator solvents (with quite different polarities) and, in some cases, p-tert-octylphenol (TOP) as additive. The latter was used regarding a possible increase in selectivity. The general working characteristics of all prepared electrodes were evaluated in a low dispersion flow injection analysis (FIA) manifold by injecting 500µl of citrate standard solutions into an ionic strength (IS) adjuster carrier (10−2 mol l−1) flowing at 3ml min−1. Good potentiometric response, with an average slope and a repeatability of 61.9mV per decade and ±0.8%, respectively, resulted from selective membranes comprising additive and bis(2-ethylhexyl)sebacate (bEHS) as mediator solvent. The same membranes conducted as well to the best selectivity characteristics, assessed by the separated solutions method and for several chemical species, such as chloride, nitrate, ascorbate, glucose, fructose and sucrose. Pharmaceutical preparations, soft drinks and beers were analyzed under conditions that enabled simultaneous pH and ionic strength adjustment (pH = 3.2; ionic strength = 10−2 mol l−1), and the attained results agreed well with the used reference method (relative error < 4%). The above experimental conditions promoted a significant increase in sensitivity of the potentiometric response, with a supra-Nernstian slope of 80.2mV per decade, and allowed the analysis of about 90 samples per hour, with a relative standard deviation <1.0%.
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A new flow-injection analytical procedure is proposed for the determination of the total amount of polyphenols in wines; the method is based on the formation of a colored complex between 4-aminoantipyrine and phenols, in the presence of an oxidizing reagent. The oxidizing agents hexacyanoferrate(III), peroxodisulfate, and tetroxoiodate(VII) were tested. Batch trials were first performed to select appropriate oxidizing agents, pH, and concentration ratios of reagents, on the basis of their effect on the stability of the colored complex. Conditions selected as a result of these trials were implemented in a flow-injection analytical system in which the influence of injection volume, flow rate, and reaction- coil length, was evaluated. Under the optimum conditions the total amount of polyphenols, expressed as gallic acid, could be determined within a concentration range of 36 to 544 mg L–1, and with a sensitivity of 344 L mol–1 cm–1 and an RSD <1.1%. The reproducibility of analytical readings was indicative of standard deviations <2%. Interference from sugars, tartaric acid, ascorbic acid, methanol, ammonium sulfate, and potassium chloride was negligible. The proposed system was applied to the determination of total polyphenols in red wines, and enabled analysis of approximately 55 samples h–1. Results were usually precise and accurate; the RSD was <3.9% and relative errors, by the Folin–Ciocalteu method, <5.1%.
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Seismic data is difficult to analyze and classical mathematical tools reveal strong limitations in exposing hidden relationships between earthquakes. In this paper, we study earthquake phenomena in the perspective of complex systems. Global seismic data, covering the period from 1962 up to 2011 is analyzed. The events, characterized by their magnitude, geographic location and time of occurrence, are divided into groups, either according to the Flinn-Engdahl (F-E) seismic regions of Earth or using a rectangular grid based in latitude and longitude coordinates. Two methods of analysis are considered and compared in this study. In a first method, the distributions of magnitudes are approximated by Gutenberg-Richter (G-R) distributions and the parameters used to reveal the relationships among regions. In the second method, the mutual information is calculated and adopted as a measure of similarity between regions. In both cases, using clustering analysis, visualization maps are generated, providing an intuitive and useful representation of the complex relationships that are present among seismic data. Such relationships might not be perceived on classical geographic maps. Therefore, the generated charts are a valid alternative to other visualization tools, for understanding the global behavior of earthquakes.
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Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.
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Global warming and the associated climate changes are being the subject of intensive research due to their major impact on social, economic and health aspects of the human life. Surface temperature time-series characterise Earth as a slow dynamics spatiotemporal system, evidencing long memory behaviour, typical of fractional order systems. Such phenomena are difficult to model and analyse, demanding for alternative approaches. This paper studies the complex correlations between global temperature time-series using the Multidimensional scaling (MDS) approach. MDS provides a graphical representation of the pattern of climatic similarities between regions around the globe. The similarities are quantified through two mathematical indices that correlate the monthly average temperatures observed in meteorological stations, over a given period of time. Furthermore, time dynamics is analysed by performing the MDS analysis over slices sampling the time series. MDS generates maps describing the stations’ locus in the perspective that, if they are perceived to be similar to each other, then they are placed on the map forming clusters. We show that MDS provides an intuitive and useful visual representation of the complex relationships that are present among temperature time-series, which are not perceived on traditional geographic maps. Moreover, MDS avoids sensitivity to the irregular distribution density of the meteorological stations.
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This paper presents a novel method for the analysis of nonlinear financial and economic systems. The modeling approach integrates the classical concepts of state space representation and time series regression. The analytical and numerical scheme leads to a parameter space representation that constitutes a valid alternative to represent the dynamical behavior. The results reveal that business cycles can be clearly revealed, while the noise effects common in financial indices can elegantly be filtered out of the results.
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OBJECTIVE To analyze the prevalence of IgG antibodies to Toxoplasma gondii in patients infected with HIV/AIDS and the association of demographic and social variables. METHODS Descriptive cross-sectional study that included the analysis of sociodemographic data and laboratory findings of 200 patients infected with HIV/AIDS treated in a laboratory unit in Maputo, Mozambique, in 2010. Individual data for all participants were collected with a self-administered questionnaire. Plasma samples were tested for IgG testing of anti- T. gondii using hemagglutination for the analysis of antibodies. RESULTS The seroprevalence of IgG anti- T. gondii was 46.0% (95%CI 39.2;52.9), 39.3% (95%CI 29.5;50.0) in men and 50.9% (95%CI 41.9;59.8) in women, with no difference between sex (OR 1.30; 95%CI 0.95;1.77; p = 0.12). Ages ranged from 10 to 60 years, with a higher prevalence of infection in older age groups, but with no significant difference between them. Regularly consuming cattle meat (OR 1.74; 95%CI 1.04;2.89, p = 0.05), breeding cats/dogs (OR 6.18; 95%CI 3.60;10.62, p < 0.000) and having regular contact with soil (OR 3.38; 95%CI 2.19;5.21; p < 0.000) were significantly associated with risk of latent infection. CONCLUSIONS Toxoplasmosis is an infection with high prevalence in Mozambique. Cultural and behavioral aspects increase the risk. Toxoplasmosis can be responsible in our environment by the great burden of morbidity and mortality associated with meningoencephalic injuries in patients with HIV/AIDS.
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The goal of this study is to analyze the dynamical properties of financial data series from nineteen worldwide stock market indices (SMI) during the period 1995–2009. SMI reveal a complex behavior that can be explored since it is available a considerable volume of data. In this paper is applied the window Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional order systems.