220 resultados para correlation pattern


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Eutectic growth is an interesting example for exploring the topic of pattern-formation in multi-phase systems, where the growth of the phases is coupled with the diffusive transport of one or more components in the melt. While in the case of binary alloys, the number of possibilities are limited (lamellae, rods, labyrinth etc.), their number rapidly increases with the number of components and phases. In this paper, we will investigate pattern formation during three-phase eutectic solidification using a state-of-the art phase-field method based on the grand-canonical density formulation. The major aim of the study is to highlight the role of two properties, which are the volume fraction of the solid phases and the solid-liquid interfacial energies, in the self-organization of the solid phases during directional growth. Thereafter, we will show representative phase-field simulations of a micro-structure in a real alloy (Ag-Al-Cu) using an asymmetric phase diagram as well as interfacial properties.

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A new monoclinic polymorph, form II (P2(1)/c, Z = 4), has been isolated for 3,4-dimethoxycinnamic acid (DMCA). Its solid-state 2 + 2 photoreaction to the corresponding alpha-truxillic acid is different from that of the first polymorph, the triclinic form I (P (1) over bar, Z = 4) that was reported in 1984. The crystal structures of the two forms are rather different. The two polymorphs also exhibit different photomechanical properties. Form I exhibits photosalient behavior but this effect is absent in form II. These properties can be explained on the basis of the crystal packing in the two forms. The nanoindentation technique is used to shed further insights into these structure-property relationships. A faster photoreaction in form I and a higher yield in form II are rationalized on the basis of the mechanical properties of the individual crystal forms. It is suggested that both Schmidt-type and Kaupp-type topochemistry are applicable for the solid-state trans-cinnamic acid photodimerization reaction. Form I of DMCA is more plastic and seems to react under Kaupp-type conditions with maximum molecular movements. Form II is more brittle, and its interlocked structure seems to favor Schmidt-type topochemistry with minimum molecular movement.

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Climate change is expected to influence extreme precipitation which in turn might affect risks of pluvial flooding. Recent studies on extreme rainfall over India vary in their definition of extremes, scales of analyses and conclusions about nature of changes in such extremes. Fingerprint-based detection and attribution (D&A) offer a formal way of investigating the presence of anthropogenic signals in hydroclimatic observations. There have been recent efforts to quantify human effects in the components of the hydrologic cycle at large scales, including precipitation extremes. This study conducts a D&A analysis on precipitation extremes over India, considering both univariate and multivariate fingerprints, using a standardized probability-based index (SPI) from annual maximum one-day (RX1D) and five-day accumulated (RX5D) rainfall. The pattern-correlation based fingerprint method is used for the D&A analysis. Transformation of annual extreme values to SPI and subsequent interpolation to coarser grids are carried out to facilitate comparison between observations and model simulations. Our results show that in spite of employing these methods to address scale and physical processes mismatch between observed and model simulated extremes, attributing changes in regional extreme precipitation to anthropogenic climate change is difficult. At very high (95%) confidence, no signals are detected for RX1D, while for the RX5D and multivariate cases only the anthropogenic (ANT) signal is detected, though the fingerprints are in general found to be noisy. The findings indicate that model simulations may underestimate regional climate system responses to increasing human forcings for extremes, and though anthropogenic factors may have a role to play in causing changes in extreme precipitation, their detection is difficult at regional scales and not statistically significant. (C) 2015 Elsevier B.V. All rights reserved.

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Using coherent light interrogating a turbid object perturbed by a focused ultrasound (US) beam, we demonstrate localized measurement of dynamics in the focal region, termed the region-of-interest (ROI), from the decay of the modulation in intensity autocorrelation of light. When the ROI contains a pipe flow, the decay is shown to be sensitive to the average flow velocity from which the mean-squared displacement (MSD) of the scattering centers in the flow can be estimated. While the MSD estimated is seen to be an order of magnitude higher than that obtainable through the usual diffusing wave spectroscopy (DWS) without the US, it is seen to be more accurate as verified by the volume flow estimated from it. It is further observed that, whereas the MSD from the localized measurement grows with time as tau(alpha) with alpha approximate to 1.65, without using the US, a is seen to be much less. Moreover, with the local measurement, this super-diffusive nature of the pipe flow is seen to persist longer, i.e., over a wider range of initial tau, than with the unassisted DWS. The reason for the super-diffusivity of flow, i.e., alpha < 2, in the ROI is the presence of a fluctuating (thermodynamically nonequilibrium) component in the dynamics induced by the US forcing. Beyond this initial range, both methods measure MSDs that rise linearly with time, indicating that ballistic and near-ballistic photons hardly capture anything beyond the background Brownian motion. (C) 2015 Optical Society of America

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Melt spun ribbons of Fe95-x Zr (x) B4Cu1 with x = 7 (Z7B4) and 9 (Z9B4) alloys have been prepared, and their structure and magnetic properties have been evaluated using XRD, DSC, TEM, VSM, and Mossbauer spectroscopy. The glass forming ability (GFA) of both alloys has been calculated theoretically using thermodynamical parameters, and Z9B4 alloy is found to possess higher GFA than that of Z7B4 alloy which is validated by XRD results. On annealing, the amorphous Z7B4 ribbon crystallizes into nanocrystalline alpha-Fe, whereas amorphous Z9B4 ribbon shows two-stage crystallization process, first partially to bcc solid solution which is then transformed to nanocrystalline alpha-Fe and Fe2Zr phases exhibiting bimodal distribution. A detailed phase analysis using Mossbauer spectroscopy through hyperfine field distribution of phases has been carried out to understand the crystallization behavior of Z7B4 and Z9B4 alloy ribbons. In order to understand the phase transformation behavior of Z7B4 and Z9B4 ribbons, molar Gibbs free energies of amorphous, alpha-Fe, and Fe2Zr phases have been evaluated. It is found that in case of Z7B4, alpha-Fe is always a stable phase, whereas Fe2Zr is stable at higher temperature for Z9B4. (C) The Minerals, Metals & Materials Society and ASM International 2015

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Aerosol loading over the South Asian region has the potential to affect the monsoon rainfall, Himalayan glaciers and regional air-quality, with implications for the billions in this region. While field campaigns and network observations provide primary data, they tend to be location/season specific. Numerical models are useful to regionalize such location-specific data. Studies have shown that numerical models underestimate the aerosol scenario over the Indian region, mainly due to shortcomings related to meteorology and the emission inventories used. In this context, we have evaluated the performance of two such chemistry-transport models: WRF-Chem and SPRINTARS over an India-centric domain. The models differ in many aspects including physical domain, horizontal resolution, meteorological forcing and so on etc. Despite these differences, both the models simulated similar spatial patterns of Black Carbon (BC) mass concentration, (with a spatial correlation of 0.9 with each other), and a reasonable estimates of its concentration, though both of them under-estimated vis-a-vis the observations. While the emissions are lower (higher) in SPRINTARS (WRF-Chem), overestimation of wind parameters in WRF-Chem caused the concentration to be similar in both models. Additionally, we quantified the under-estimations of anthropogenic BC emissions in the inventories used these two models and three other widely used emission inventories. Our analysis indicates that all these emission inventories underestimate the emissions of BC over India by a factor that ranges from 1.5 to 2.9. We have also studied the model simulations of aerosol optical depth over the Indian region. The models differ significantly in simulations of AOD, with WRF-Chem having a better agreement with satellite observations of AOD as far as the spatial pattern is concerned. It is important to note that in addition to BC, dust can also contribute significantly to AOD. The models differ in simulations of the spatial pattern of mineral dust over the Indian region. We find that both meteorological forcing and emission formulation contribute to these differences. Since AOD is column integrated parameter, description of vertical profiles in both models, especially since elevated aerosol layers are often observed over Indian region, could be also a contributing factor. Additionally, differences in the prescription of the optical properties of BC between the models appear to affect the AOD simulations. We also compared simulation of sea-salt concentration in the two models and found that WRF-Chem underestimated its concentration vis-a-vis SPRINTARS. The differences in near-surface oceanic wind speeds appear to be the main source of this difference. In-spite of these differences, we note that there are similarities in their simulation of spatial patterns of various aerosol species (with each other and with observations) and hence models could be valuable tools for aerosol-related studies over the Indian region. Better estimation of emission inventories could improve aerosol-related simulations. (C) 2015 Elsevier Ltd. All rights reserved.

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Healthy human skin harbours a diverse array of microbes that comprise the skin microbiome. Commensal bacteria constitute an important component of resident microbiome and are intricately linked to skin health. Recent studies describe an association between altered skin microbial community and epidemiology of diseases, like psoriasis, atopic dermatitis etc. In this study, we compare the differences in bacterial community of lesional and non-lesional skin of vitiligo subjects. Our study reveals dysbiosis in the diversity of microbial community structure in lesional skin of vitiligo subjects. Although individual specific signature is dominant over the vitiligo-specific microbiota, a clear decrease in taxonomic richness and evenness can be noted in lesional patches. Investigation of community specific correlation networks reveals distinctive pattern of interactions between resident bacterial populations of the two sites (lesional and non-lesional). While Actinobacterial species constitute the central regulatory nodes (w.r.t. degree of interaction) in non-lesional skin, species belonging to Firmicutes dominate on lesional sites. We propose that the changes in taxonomic characteristics of vitiligo lesions, as revealed by our study, could play a crucial role in altering the maintenance and severity of disease. Future studies would elucidate mechanistic relevance of these microbial dynamics that can provide new avenues for therapeutic interventions.

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Nanoparticle deposition behavior observed at the Darcy scale represents an average of the processes occurring at the pore scale. Hence, the effect of various pore-scale parameters on nanoparticle deposition can be understood by studying nanoparticle transport at pore scale and upscaling the results to the Darcy scale. In this work, correlation equations for the deposition rate coefficients of nanoparticles in a cylindrical pore are developed as a function of nine pore-scale parameters: the pore radius, nanoparticle radius, mean flow velocity, solution ionic strength, viscosity, temperature, solution dielectric constant, and nanoparticle and collector surface potentials. Based on dominant processes, the pore space is divided into three different regions, namely, bulk, diffusion, and potential regions. Advection-diffusion equations for nanoparticle transport are prescribed for the bulk and diffusion regions, while the interaction between the diffusion and potential regions is included as a boundary condition. This interaction is modeled as a first-order reversible kinetic adsorption. The expressions for the mass transfer rate coefficients between the diffusion and the potential regions are derived in terms of the interaction energy profile. Among other effects, we account for nanoparticle-collector interaction forces on nanoparticle deposition. The resulting equations are solved numerically for a range of values of pore-scale parameters. The nanoparticle concentration profile obtained for the cylindrical pore is averaged over a moving averaging volume within the pore in order to get the 1-D concentration field. The latter is fitted to the 1-D advection-dispersion equation with an equilibrium or kinetic adsorption model to determine the values of the average deposition rate coefficients. In this study, pore-scale simulations are performed for three values of Peclet number, Pe = 0.05, 5, and 50. We find that under unfavorable conditions, the nanoparticle deposition at pore scale is best described by an equilibrium model at low Peclet numbers (Pe = 0.05) and by a kinetic model at high Peclet numbers (Pe = 50). But, at an intermediate Pe (e.g., near Pe = 5), both equilibrium and kinetic models fit the 1-D concentration field. Correlation equations for the pore-averaged nanoparticle deposition rate coefficients under unfavorable conditions are derived by performing a multiple-linear regression analysis between the estimated deposition rate coefficients for a single pore and various pore-scale parameters. The correlation equations, which follow a power law relation with nine pore-scale parameters, are found to be consistent with the column-scale and pore-scale experimental results, and qualitatively agree with the colloid filtration theory. These equations can be incorporated into pore network models to study the effect of pore-scale parameters on nanoparticle deposition at larger length scales such as Darcy scale.

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Self-assembly has been recognized as an efficient tool for generating a wide range of functional, chemically, or physically textured surfaces for applications in small scale devices. In this work, we investigate the stability of thin films of polymer solutions. For low concentrations of polymer in the solution, long length scale dewetting patterns are obtained with wavelength approximately few microns. Whereas, for concentrations above a critical value, bimodal dispersion curves are obtained with the dominant wavelength being up to two orders smaller than the usual dewetting length scale. We further show that the short wavelength corresponds to the phase separation in the film resulting in uniformly distributed high and low concentration regions. Interestingly, due to the solvent entropy, at very high concentration values of polymer, a re-entrant behaviour is observed with the dominant length scale now again corresponding to the dewetting wavelength. Thus, we show that the binary films of polymer solutions provide additional control parameters that can be utilized for generating functional textured surfaces for various applications. (C) 2016 AIP Publishing LLC.

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The utility of canonical correlation analysis (CCA) for domain adaptation (DA) in the context of multi-view head pose estimation is examined in this work. We consider the three problems studied in 1], where different DA approaches are explored to transfer head pose-related knowledge from an extensively labeled source dataset to a sparsely labeled target set, whose attributes are vastly different from the source. CCA is found to benefit DA for all the three problems, and the use of a covariance profile-based diagonality score (DS) also improves classification performance with respect to a nearest neighbor (NN) classifier.