998 resultados para Skin Modelling


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Ultrasonication of aqueous KI solution is known to yield I2 due to reaction of iodide ions with hydroxyl radicals, which in turn are generated due to cavitation. Based on this conceptual framework, a model has been developed to predict the rate of iodine formation for KI solutions of various concentrations under different gas atmospheres. The model follows the growth and collapse of a gas—vapour cavity using the Rayleigh—Plesset bubble dynamics equation. The bubble is assumed to behave isothermally during its growth phase and a part of the collapse phase. Thereafter it is assumed to collapse adiabatically, yielding high temperatures and pressures. Thermodynamic equilibrium is assumed in the bubble at the end of collapse phase. The contents of the bubble are assumed to mix with the liquid, and the reactor contents are assumed to be well stirred. The model has been verified by conducting experiments with KI solutions of different concentrations and using different gas atmospheres. The model not only explains these results but also the existence of a maximum when Ar---O2 mixtures of different compositions are employed.

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Ultrasonication of aqueous KI solution is known to yield I2 due to reaction of iodide ions with hydroxyl radicals, which in turn are generated due to cavitation. Based on this conceptual framework, a model has been developed to predict the rate of iodine formation for KI solutions of various concentrations under different gas atmospheres. The model follows the growth and collapse of a gas-vapour cavity using the Rayleigh-Plesset bubble dynamics equation. The bubble is assumed to behave isothermally during its growth phase and a part of the collapse phase. Thereafter it is assumed to collapse adiabatically, yielding high temperatures and pressures. Thermodynamic equilibrium is assumed in the bubble at the end of collapse phase. The contents of the bubble are assumed to mix with the liquid, and the reactor contents are assumed to be well stirred. The model has been verified by conducting experiments with KI solutions of different concentrations and using different gas atmospheres. The model not only explains these results but also the existence of a maximum when Ar-O2 mixtures of different compositions are employed.

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This study describes two machine learning techniques applied to predict liquefaction susceptibility of soil based on the standard penetration test (SPT) data from the 1999 Chi-Chi, Taiwan earthquake. The first machine learning technique which uses Artificial Neural Network (ANN) based on multi-layer perceptions (MLP) that are trained with Levenberg-Marquardt backpropagation algorithm. The second machine learning technique uses the Support Vector machine (SVM) that is firmly based on the theory of statistical learning theory, uses classification technique. ANN and SVM have been developed to predict liquefaction susceptibility using corrected SPT (N-1)(60)] and cyclic stress ratio (CSR). Further, an attempt has been made to simplify the models, requiring only the two parameters (N-1)(60) and peck ground acceleration (a(max)/g)], for the prediction of liquefaction susceptibility. The developed ANN and SVM models have also been applied to different case histories available globally. The paper also highlights the capability of the SVM over the ANN models.

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Joining of dissimilar metals involves a number of scientific issues, the modelling of which offers unique challenges. This review discusses the complexities in different joining processes and dissimilar combinations, and the corresponding computational techniques that have the potential to address the same. Future directions in modelling at both macroscopic and microscopic scales are also suggested.

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Mathematical modelling plays a vital role in the design, planning and operation of flexible manufacturing systems (FMSs). In this paper, attention is focused on stochastic modelling of FMSs using Markov chains, queueing networks, and stochastic Petri nets. We bring out the role of these modelling tools in FMS performance evaluation through several illustrative examples and provide a critical comparative evaluation. We also include a discussion on the modelling of deadlocks which constitute an important source of performance degradation in fully automated FMSs.

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This paper presents the results of a thermodynamic cycle analysis of single stage resorption heat pump (RHP) and resorption heat transformer (RHT) cycles with the new working pairs R22-NMP and R22-DMA. The coefficients of performance (COP) are correlated with the low grade source temperature, temperature at which useful heat is obtained and ambient temperature. The COPs are in the range 1.20–1.60 for the RHP mode and 0.25–0.45 for the RHT mode. Absorber temperatures (useful temperatures) as high as 50°C in the RHP mode and 87°C in the RHT mode have been obtained. It is observed that absorption-resorption systems are inflexible in their range of operating temperature and necessitate a higher pump work as compared with simple single-stage absorption heating systems. However, single stage RHTs show higher temperature boosts than simple absorption heat transformers.

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The basic concepts and techniques involved in the development and analysis of mathematical models for individual neurons and networks of neurons are reviewed. Some of the interesting results obtained from recent work in this field are described. The current status of research in this field in India is discussed

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We present here a critical assessment of two vortex approaches (both two-dimensional) to the modelling of turbulent mixing layers. In the first approach the flow is represented by point vortices, and in the second it is simulated as the evolution of a continuous vortex sheet composed of short linear elements or ''panels''. The comparison is based on fresh simulations using approximately the same number of elements in either model, paying due attention in both to the boundary conditions far downstream as well as those on the splitter plate from which the mixing layer issues. The comparisons show that, while both models satisfy the well-known invariants of vortex dynamics approximately to the same accuracy, the vortex panel model, although ultimately not convergent, leads to smoother roll-up and values of stresses and moments that are in closer agreement with the experiment, and has a higher computational efficiency for a given degree of convergence on moments. The point vortex model, while faster for a given number of elements, produces an unsatisfactory roll-up which (for the number of elements used) is rendered worse by the incorporation of the Van der Vooren correction for sheet curvature.

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A pseudo 2-D mathematical model has been developed to simulate a cupola with one row and two rows of tuyere. The simulation results predicted higher spout temperature and combustion ratio for cupola with two rows of tuyere compared to that with one row. Further, the model has been used to study the effect of the distance of separation between the two rows of tuyere on cupola performance. The computed results shows that the spout temperature increases with tuyere level separation and attains the maximum at an optimum distance of separation between two rows of tuyere. Above the optimum, the spout temperature starts decreasing. The exit gas temperature and combustion ratio increases monotonously with the increase in tuyere level separation. These results agree well with the reported experimental observations. The mechanism behind the improved cupola performance with two rows of tuyere has been deduced from the computed temperature and composition profiles inside the cupola.

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The review is concerned with models that analyze transport:processes that occur during microwave heating. Early models on microwave. heating used Lambert's law to describe the microwave power absorption. Over the last decade, models for transport processes have been developed with the microwave power derived from Maxwell's equations. Those models, primarily based on plane waves, have been used for analyzing microwave heating of solids, liquids, emulsions, microwave thawing and drying. The models illustrate phenomena such a resonances, hot spots, edge and runaway heating. The literature on microwave sintering, susceptor heating and microwave assisted synthesis is largely experimental in nature and only key issues are highlighted. To fully appreciate the models for microwave heating, a section on the theory of electromagnetic wave propagation is included, where expressions for the electric field in dielectric slabs and cylinders are presented.

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Background and purpose of the study: Herbal enhancers compared to the synthetic ones have shown less toxis effects. Coumarins have been shown at concentrations inhibiting phospoliphase C-Y (Phc-Y) are able to enhance tight junction (TJ) permeability due to hyperpoalation of Zonolous Occludense-1 (ZO-1) proteins. The purpose of this study was to evaluate the influence of ethanolic extract of Angelica archengelica (AA-E) which contain coumarin on permeation of repaglinide across rat epidermis and on the tight junction plaque protein ZO-1 in HaCaT cells. Methods: Transepidermal water loss (TEWL) from the rat skin treated with different concentrations of AA-E was assessed by Tewameter. Scanning and Transmission Electron Microscopy (TEM) on were performed on AA-E treated rat skin portions. The possibility of AA-E influence on the architecture of tight junctions by adverse effect on the cytoplasmic ZO-1 in HaCaT cells was investigated. Finally, the systemic delivery of repaglinide from the optimized transdermal formulation was investigated in rats. Results: The permeation of repaglinide across excised rat epidermis was 7-fold higher in the presence of AA-E (5% w/v) as compared to propylene glycol:ethanol (7:3) mixture. The extract was found to perturb the lipid microconstituents in both excised and viable rat skin, although, the effect was less intense in the later. The enhanced permeation of repaglinide across rat epidermis excised after treatment with AA-E (5% w/v) for different periods was in concordance with the high TEWL values of similarly treated viable rat skin. Further, the observed increase in intercellular space, disordering of lipid structure and corneocyte detachment indicated considerable effect on the ultrastructure of rat epidermis. Treatment of HaCaT cell line with AA-E (0.16% w/v) for 6 hrs influenced ZO-1 as evidenced by reduced immunofluorescence of anti-TJP1 (ZO-1) antibody in Confocal Laser Scanning Microscopy studies (CLSM) studies. The plasma concentration of repaglinide from transdermal formulation was maintained higher and for longer time as compared to oral administration of repaglinide. Major conclusion: Results suggest the overwhelming influence of Angelica archengelica in enhancing the percutaneous permeation of repaglinide to be mediated through perturbation of skin lipids and tight junction protein (ZO-1).

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It is well known that the increasing space activities pose a serious threat to future missions. This is mainly due to the presence of spent stages, rockets spacecraft and fragments which can lead to collisions. The calculation of the collision probability of future space vehicles with the orbital debris is necessary for estimating the risk. There is lack of adequately catalogued and openly available detailed information on the explosion characteristics of trackable and untrackable debris data. Such a situation compels one to develop suitable mathematical modelling of the explosion and the resultant debris environment. Based on a study of the available information regarding the fragmentation, subsequent evolution and observation, it turns out to be possible to develop such a mathematical model connecting the dynamical features of the fragmentation with the geometrical/orbital characteristics of the debris and representing the environment through the idea of equivalent breakup. (C) 1997 COSPAR.

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The next generation manufacturing technologies will draw on new developments in geometric modelling. Based on a comprehensive analysis of the desiderata of next generation geometric modellers, we present a critical review of the major modelling paradigms, namely, CSG, B-Rep, non-manifold, and voxel models. We present arguments to support the view that voxel-based modellers have attributes that make it the representation scheme of choice in meeting the emerging requirements of geometric modelling.

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Models for electricity planning require inclusion of demand. Depending on the type of planning, the demand is usually represented as an annual demand for electricity (GWh), a peak demand (MW) or in the form of annual load-duration curves. The demand for electricity varies with the seasons, economic activities, etc. Existing schemes do not capture the dynamics of demand variations that are important for planning. For this purpose, we introduce the concept of representative load curves (RLCs). Advantages of RLCs are demonstrated in a case study for the state of Karnataka in India. Multiple discriminant analysis is used to cluster the 365 daily load curves for 1993-94 into nine RLCs. Further analyses of these RLCs help to identify important factors, namely, seasonal, industrial, agricultural, and residential (water heating and air-cooling) demand variations besides rationing by the utility. (C) 1999 Elsevier Science Ltd. All rights reserved.