163 resultados para optic properties analysis


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A novel near-infrared spectroscopy (NIRS) method has been researched and developed for the simultaneous analyses of the chemical components and associated properties of mint (Mentha haplocalyx Briq.) tea samples. The common analytes were: total polysaccharide content, total flavonoid content, total phenolic content, and total antioxidant activity. To resolve the NIRS data matrix for such analyses, least squares support vector machines was found to be the best chemometrics method for prediction, although it was closely followed by the radial basis function/partial least squares model. Interestingly, the commonly used partial least squares was unsatisfactory in this case. Additionally, principal component analysis and hierarchical cluster analysis were able to distinguish the mint samples according to their four geographical provinces of origin, and this was further facilitated with the use of the chemometrics classification methods-K-nearest neighbors, linear discriminant analysis, and partial least squares discriminant analysis. In general, given the potential savings with sampling and analysis time as well as with the costs of special analytical reagents required for the standard individual methods, NIRS offered a very attractive alternative for the simultaneous analysis of mint samples.

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This paper demonstrates the procedures for probabilistic assessment of a pesticide fate and transport model, PCPF-1, to elucidate the modeling uncertainty using the Monte Carlo technique. Sensitivity analyses are performed to investigate the influence of herbicide characteristics and related soil properties on model outputs using four popular rice herbicides: mefenacet, pretilachlor, bensulfuron-methyl and imazosulfuron. Uncertainty quantification showed that the simulated concentrations in paddy water varied more than those of paddy soil. This tendency decreased as the simulation proceeded to a later period but remained important for herbicides having either high solubility or a high 1st-order dissolution rate. The sensitivity analysis indicated that PCPF-1 parameters requiring careful determination are primarily those involve with herbicide adsorption (the organic carbon content, the bulk density and the volumetric saturated water content), secondary parameters related with herbicide mass distribution between paddy water and soil (1st-order desorption and dissolution rates) and lastly, those involving herbicide degradations. © Pesticide Science Society of Japan.

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Finite element analysis (FEA) models of uniaxial loading of pumpkin peel and flesh tissues were developed and validated using experimental results. The tensile model was developed for both linear elastic and plastic material models, the compression model was develop d only with the plastic material model. The outcomes of force versus time curves obtained from FEA models followed similar pattern to the experimental curves however the curve resulted with linear elastic material properties had a higher difference with the experimental curves. The values of predicted forces were determined and compared with the experimental curve. An error indicator was introduced and computed for each case and compared. Additionally Root Mean Square Error (RMSE) values were also calculated for each model and compared. The results of modelling were used to develop material model for peel and flesh tissues in FEA modelling of mechanical peeling of tough skinned vegetables.

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We made a retrospective analysis of the efficacy and complication rate of 268 esophageal dilatation procedures performed under fluoroscopic control using the fiber-optic endoscope in 45 children with esophageal stricture. Antegrade and retrograde stricture dilatation was performed under general anesthetic, mainly as an outpatient procedure. Thirty-six children had an esophageal stricture following tracheoesophageal fistula and/or esophageal atresia repair, and nine children had severe corrosive stricture of the esophagus following lye ingestion. The procedure was well tolerated and effective. © 1992 Raven Press, Ltd., New York.

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Quantifying the stiffness properties of soft tissues is essential for the diagnosis of many cardiovascular diseases such as atherosclerosis. In these pathologies it is widely agreed that the arterial wall stiffness is an indicator of vulnerability. The present paper focuses on the carotid artery and proposes a new inversion methodology for deriving the stiffness properties of the wall from cine-MRI (magnetic resonance imaging) data. We address this problem by setting-up a cost function defined as the distance between the modeled pixel signals and the measured ones. Minimizing this cost function yields the unknown stiffness properties of both the arterial wall and the surrounding tissues. The sensitivity of the identified properties to various sources of uncertainty is studied. Validation of the method is performed on a rubber phantom. The elastic modulus identified using the developed methodology lies within a mean error of 9.6%. It is then applied to two young healthy subjects as a proof of practical feasibility, with identified values of 625 kPa and 587 kPa for one of the carotid of each subject.

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A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.

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Gulland's [Gulland, J.A., 1965. Estimation of mortality rates. Annex to Arctic Fisheries Working Group Report (meeting in Hamburg, January 1965). ICES. C.M. 1965, Doc. No. 3 (mimeographed)] virtual population analysis (VPA) is commonly used for studying the dynamics of harvested fish populations. However, it necessitates the solving of a nonlinear equation for the instantaneous rate of fishing mortality of the fish in a population. Pope [Pope, J.G., 1972. An investigation of the accuracy of Virtual Population Analysis using cohort analysis. ICNAF Res. Bull. 9, 65-74. Also available in D.H. Cushing (ed.) (1983), Key Papers on Fish Populations, p. 291-301, IRL Press, Oxford, 405 p.] eliminated this necessity in his cohort analysis by approximating its underlying age- and time-dependent population model. His approximation has since become one of the most commonly used age- and time-dependent fish population models in fisheries science. However, some of its properties are not well understood. For example, many assert that it describes the dynamics of a fish population, from which the catch of fish is taken instantaneously in the middle of the year. Such an assertion has never been proven, nor has its implied instantaneous rate of fishing mortality of the fish of a particular age at a particular time been examined, nor has its implied catch equation been derived from a general catch equation. In this paper, we prove this assertion, examine its implied instantaneous rate of fishing mortality of the fish of a particular age at a particular time, derive its implied catch equation from a general catch equation, and comment on how to structure an age- and time-dependent population model to ensure its internal consistency. This work shows that Gulland's (1965) virtual population analysis and Pope's (1972) cohort analysis lie at the opposite end of a continuous spectrum as a general model for a seasonally occurring fishery; Pope's (1972) approximation implies an infinitely large instantaneous rate of fishing mortality of the fish of a particular age at a particular time in a fishing season of zero length; and its implied catch equation has an undefined instantaneous rate of fishing mortality of the fish in a population, but a well-defined cumulative instantaneous rate of fishing mortality of the fish in the population. This work also highlights a need for a more careful treatment of the times of start and end of a fishing season in fish population models.

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We propose an iterative estimating equations procedure for analysis of longitudinal data. We show that, under very mild conditions, the probability that the procedure converges at an exponential rate tends to one as the sample size increases to infinity. Furthermore, we show that the limiting estimator is consistent and asymptotically efficient, as expected. The method applies to semiparametric regression models with unspecified covariances among the observations. In the special case of linear models, the procedure reduces to iterative reweighted least squares. Finite sample performance of the procedure is studied by simulations, and compared with other methods. A numerical example from a medical study is considered to illustrate the application of the method.

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Underground tunnels are vulnerable to terrorist attacks which can cause collapse of the tunnel structures or at least extensive damage, requiring lengthy repairs. This paper treats the blast impact on a reinforced concrete segmental tunnel buried in soil under a number of parametric conditions; soil properties, soil cover, distance of explosive from the tunnel centreline and explosive weight and analyses the possible failure patterns. A fully coupled Fluid Structure Interaction (FSI) technique incorporating the Arbitrary Lagrangian-Eulerian (ALE) method is used in this study. Results indicate that the tunnel in saturated soil is more vulnerable to severe damage than that buried in either partially saturated soil or dry soil. The tunnel is also more vulnerable to surface explosions which occur directly above the centre of the tunnel than those that occur at any equivalent distances in the ground away from the tunnel centre. The research findings provide useful information on modeling, analysis, overall tunnel response and failure patterns of segmented tunnels subjected to blast loads. This information will guide future development and application of research in this field.

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The family of location and scale mixtures of Gaussians has the ability to generate a number of flexible distributional forms. The family nests as particular cases several important asymmetric distributions like the Generalized Hyperbolic distribution. The Generalized Hyperbolic distribution in turn nests many other well known distributions such as the Normal Inverse Gaussian. In a multivariate setting, an extension of the standard location and scale mixture concept is proposed into a so called multiple scaled framework which has the advantage of allowing different tail and skewness behaviours in each dimension with arbitrary correlation between dimensions. Estimation of the parameters is provided via an EM algorithm and extended to cover the case of mixtures of such multiple scaled distributions for application to clustering. Assessments on simulated and real data confirm the gain in degrees of freedom and flexibility in modelling data of varying tail behaviour and directional shape.

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In this research we modelled computer network devices to ensure their communication behaviours meet various network standards. By modelling devices as finite-state machines and examining their properties in a range of configurations, we discovered a flaw in a common network protocol and produced a technique to improve organisations' network security against data theft.

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A new procedure for the preparation of amorphous Ni-Co-B nanoparticles is reported, with a detailed investigation of their morphology by X-ray diffraction and transmission electron microscopy, as well as their magnetic properties. Many factors, such as chemical composition, anisotropy, size and shape of the particles, were controlled through chemical synthesis, resulting in the control of morphological and magnetic properties of the nanoparticles. Controlling pH values with ethylenediamine and using sodium dodecyl sulfate surfactant lowered the size of the nanoparticles to below 10 nm. Such a small structure and chemical disorder in nanocrystalline materials lead to magnetic properties that are different from those in their bulk-sized counterparts. The obtained nanoparticles can be used for different purposes, from pharmaceutical applications to implementations in different materials technology. The focus of this research is the synthesis of Ni-Co-B nanoparticles in a new way and studying the reaction of Ni-Co-B nanoparticles with Mg and B precursors and their effect on MgB2 properties. New nanostructures are formed in the reaction of Ni-Co-B nanoparticles with Mg: Mg2Ni, Co2Mg and possibly Mg2Co.

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Considered to be the next generation of heat transfer fluids, nanofluids have been receiving a growing amount of attention in the past decade despite the controversy and inconsistencies that have been reported. Nanofluids have great potential in a wide range of fields, particularly for solar thermal applications. This paper presents a comprehensive review of the literature on the enhancements in thermophysical and rheological properties resulting from experimental works conducted on molten salt nanofluids that are used in solar thermal energy systems. It was found that an increase in specific heat of 10–30% was achieved for most nanofluids and appeared independent of particle size and to an extent mass concentration. The specific heat increase was attributed to the formation of nanostructures at the solid–liquid interface and it was also noted that the aggregation of nanoparticles has detrimental effects on the specific heat increase. Thermal conductivity was also found to increase, though less consistently, ranging from 3% to 35%. Viscosity was seen to increase with the addition of nanoparticles and is dependent on the amount of aggregation of the particles. An in-depth micro level analysis of the mechanisms behind the thermophysical property changes is presented in this paper. In addition, possible trends are discussed relating to current theorised mechanisms in an attempt to explain the behaviour of molten salt nanofluids.