951 resultados para disruptive effect model


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Overhead distribution lines are often exposed to lightning overvoltages, whose waveforms vary widely and can differ substantially from the standard impulse voltage waveform (1,2 - 50). Different models have been proposed for predicting the strength of insulation subjected to impulses of non-standard waveforms. One of the most commonly used is the disruptive effect model, for which there are different methods for the estimation of the parameters required for its application. This paper aims at evaluating the dielectric behavior of medium voltage insulators subjected to impulses of non-standard waveforms, as well as at evaluating two methods for predicting their dielectric strength against such impulses. The test results relative to the critical lightning impulse flashover voltage (U50) and the volt-time characteristics obtained for the positive and negative polarities of different voltage waveforms are presented and discussed.

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The injurious effect of nonsteroidal anti-inflammatory drugs (NSAIDs) in the small intestine was not appreciated until the widespread use of capsule endoscopy. Animal studies found that NSAID-induced small intestinal injury depends on the ability of these drugs to be secreted into the bile. Because the individual toxicity of amphiphilic bile acids and NSAIDs directly correlates with their interactions with phospholipid membranes, we propose that the presence of both NSAIDs and bile acids alters their individual physicochemical properties and enhances the disruptive effect on cell membranes and overall cytotoxicity. We utilized in vitro gastric AGS and intestinal IEC-6 cells and found that combinations of bile acid, deoxycholic acid (DC), taurodeoxycholic acid, glycodeoxycholic acid, and the NSAID indomethacin (Indo) significantly increased cell plasma membrane permeability and became more cytotoxic than these agents alone. We confirmed this finding by measuring liposome permeability and intramembrane packing in synthetic model membranes exposed to DC, Indo, or combinations of both agents. By measuring physicochemical parameters, such as fluorescence resonance energy transfer and membrane surface charge, we found that Indo associated with phosphatidylcholine and promoted the molecular aggregation of DC and potential formation of larger and isolated bile acid complexes within either biomembranes or bile acid-lipid mixed micelles, which leads to membrane disruption. In this study, we demonstrated increased cytotoxicity of combinations of bile acid and NSAID and provided a molecular mechanism for the observed toxicity. This mechanism potentially contributes to the NSAID-induced injury in the small bowel.

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Poisson distribution has often been used for count like accident data. Negative Binomial (NB) distribution has been adopted in the count data to take care of the over-dispersion problem. However, Poisson and NB distributions are incapable of taking into account some unobserved heterogeneities due to spatial and temporal effects of accident data. To overcome this problem, Random Effect models have been developed. Again another challenge with existing traffic accident prediction models is the distribution of excess zero accident observations in some accident data. Although Zero-Inflated Poisson (ZIP) model is capable of handling the dual-state system in accident data with excess zero observations, it does not accommodate the within-location correlation and between-location correlation heterogeneities which are the basic motivations for the need of the Random Effect models. This paper proposes an effective way of fitting ZIP model with location specific random effects and for model calibration and assessment the Bayesian analysis is recommended.

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In an attempt to generate supramolecular assemblies able to function as self-healing hydrogels, a novel ureido-pyrimidinone (UPy) monomer, 2-(N ′-methacryloyloxyethylureido)-6-(1-adamantyl)-4[1H]-pyrimidinone, was synthesized and then copolymerized with N,N-dimethylacrylamide at four different feed compositions, using a solution of lithium chloride in N,N-dimethylacetamide as the polymerization medium. The assembling process in the resulting copolymers is based on crosslinking through the reversible quadruple hydrogen bonding between side-chain UPy modules. The adamantyl substituent was introduced in order to create a “hydrophobic pocket” that may protect the hydrogen bonds against the disruptive effect of water molecules. Upon hydration to equilibrium, all copolymers generated typical hydrogels when their concentration in the hydrated system was at least 15%. The small-deformation rheometry showed that all hydrated copolymers were hydrogels that maintained a solid-like behavior, and that their extrusion through a syringe needle did not affect significantly this behavior, suggesting a self-healing capacity in these materials. An application as injectable substitutes for the eye's vitreous humor was proposed

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The aim of this study is to obtain the fracture characteristics of low and medium compressive strength self consolidating concrete (SCC) for notched and un-notched plain concrete beams by using work of fracture G(F) and size effect model G(f) methods and comparing them with those of normal concrete and high performance concrete. The results show that; (i) with an increase in compressive strength, G(F) increases and G(f) decreases; (ii) with an increase in depth of beam, the decrease in nominal stress of notched beam is more when compared with that of a notchless beam.

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This article presents the details of estimation of fracture parameters for high strength concrete (HSC, HSC1) and ultra high strength concrete (UHSC). Brief details about characterization of ingredients of HSC, HSC1 and UHSC have been provided. Experiments have been carried out on beams made up of HSC, HSC1 and UHSC considering various sizes and notch depths. Fracture characteristics such as size independent fracture energy (G(f)), size of fracture process zone (C-f), fracture toughness (K-IC) and crack tip opening displacement (CTODc) have been estimated based on the experimental observations. From the studies, it is observed that (i) UHSC has high fracture energy and ductility inspite of having a very low value of C-f; (ii) relatively much more homogeneous than other concretes, because of absence of coarse aggregates and well-graded smaller size particles; (iii) the critical SIF (K-IC) values are increasing with increase of beam depth and decreasing with increase of notch depth. Generally, it can be noted that there is significant increase in fracture toughness and CTODc. They are about 7 times in HSC1 and about 10 times in UHSC compared to those in HSC; (iv) for notch-to-depth ratio 0.1, Bazant's size effect model slightly overestimates the maximum failure loads compared to experimental observations and Karihaloo's model slightly underestimates the maximum failure loads. For the notch-to-depth ratio ranging from 0.2 to 0.4 for the case of UHSC, it can be observed that, both the size effect models predict more or less similar maximum failure loads compared to corresponding experimental values.

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This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.

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Objective Levodopa in presence of decarboxylase inhibitors is following two-compartment kinetics and its effect is typically modelled using sigmoid Emax models. Pharmacokinetic modelling of the absorption phase of oral distributions is problematic because of irregular gastric emptying. The purpose of this work was to identify and estimate a population pharmacokinetic- pharmacodynamic model for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Methods The modelling involved pooling data from two studies and fixing some parameters to values found in literature (Chan et al. J Pharmacokinet Pharmacodyn. 2005 Aug;32(3-4):307-31). The first study involved 12 patients on 3 occasions and is described in Nyholm et al. Clinical Neuropharmacology 2003:26:156-63. The second study, PEDAL, involved 3 patients on 2 occasions. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Plasma samples and motor ratings (clinical assessment of motor function from video recordings on a treatment response scale between -3 and 3, where -3 represents severe parkinsonism and 3 represents severe dyskinesia.) were repeatedly collected until the clinical effect was back at baseline. At this point, the usual infusion rate was started and sampling continued for another two hours. Different structural absorption models and effect models were evaluated using the value of the objective function in the NONMEM package. Population mean parameter values, standard error of estimates (SE) and if possible, interindividual/interoccasion variability (IIV/IOV) were estimated. Results Our results indicate that Duodopa absorption can be modelled with an absorption compartment with an added bioavailability fraction and a lag time. The most successful effect model was of sigmoid Emax type with a steep Hill coefficient and an effect compartment delay. Estimated parameter values are presented in the table. Conclusions The absorption and effect models were reasonably successful in fitting observed data and can be used in simulation experiments.

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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

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We establish a fundamental equivalence between singular value decomposition (SVD) and functional principal components analysis (FPCA) models. The constructive relationship allows to deploy the numerical efficiency of SVD to fully estimate the components of FPCA, even for extremely high-dimensional functional objects, such as brain images. As an example, a functional mixed effect model is fitted to high-resolution morphometric (RAVENS) images. The main directions of morphometric variation in brain volumes are identified and discussed.

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OBJECTIVE: Bell, Marcus, and Goodlad (2013) recently conducted a meta-analysis of randomized controlled additive trials and found that adding an additional component to an existing treatment vis-à-vis the existing treatment produced larger effect sizes on targeted outcomes at 6-months follow-up than at termination, an effect they labeled as a sleeper effect. One of the limitations with Bell et al.'s detection of the sleeper effect was that they did not conduct a statistical test of the size of the effect at follow-up versus termination. METHOD: To statistically test if the differences of effect sizes between the additive conditions and the control conditions at follow-up differed from those at termination, we used a restricted maximum-likelihood random-effect model with known variances to conduct a multilevel longitudinal meta-analysis (k = 30). RESULTS: Although the small effects at termination detected by Bell et al. were replicated (ds = 0.17-0.23), none of the analyses of growth from termination to follow-up produced statistically significant effects (ds < 0.08; p > .20), and when asymmetry was considered using trim-and-fill procedure or the studies after 2000 were analyzed, magnitude of the sleeper effect was negligible (d = 0.00). CONCLUSION: There is no empirical evidence to support the sleeper effect.

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We present an approach for evaluating the efficacy of combination antitumor agent schedules that accounts for order and timing of drug administration. Our model-based approach compares in vivo tumor volume data over a time course and offers a quantitative definition for additivity of drug effects, relative to which synergism and antagonism are interpreted. We begin by fitting data from individual mice receiving at most one drug to a differential equation tumor growth/drug effect model and combine individual parameter estimates to obtain population statistics. Using two null hypotheses: (i) combination therapy is consistent with additivity or (ii) combination therapy is equivalent to treating with the more effective single agent alone, we compute predicted tumor growth trajectories and their distribution for combination treated animals. We illustrate this approach by comparing entire observed and expected tumor volume trajectories for a data set in which HER-2/neu-overexpressing MCF-7 human breast cancer xenografts are treated with a humanized, anti-HER-2 monoclonal antibody (rhuMAb HER-2), doxorubicin, or one of five proposed combination therapy schedules.

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Experimental results are presented which show that the indentation size effect for pyramidal and spherical indenters can be correlated. For a pyramidal indenter, the hardness measured in crystalline materials usually increases with decreasing depth of penetration, which is known as the indentation size effect. Spherical indentation also shows an indentation size effect. However, for a spherical indenter, hardness is not affected by depth, but increases with decreasing sphere radius. The correlation for pyramidal and spherical indenter shapes is based on geometrically necessary dislocations and work-hardening. The Nix and Gao indentation size effect model (J. Mech. Phys. Solids 46 (1998) 411) for conical indenters is extended to indenters of various shapes and compared to the experimental results. © 2002 Elsevier Science Ltd. All rights reserved.