Microstructural evolution and grain boundary sliding in a superplastic magnesium AZ31 alloy

Tensile experiments on a fine-grained single-phase Mg–Zn–Al alloy (AZ31) at 673 K revealed superplastic behavior with an elongation to failure of 475% at 1 × 10−4 s−1 and non-superplastic behavior with an elongation to failure of 160% at 1 × 10−2 s−1; the corresponding strain rate sensitivities under these conditions were 0.5 and 0.2, respectively. Measurements indicated that the grain boundary sliding (GBS) contribution to strain ξ was 30% under non-superplastic conditions; there was also a significant sharpening in texture during such deformation. Under superplastic conditions, ξ was 50% at both low and high elongations of 20% and 120%; the initial texture became more random under such conditions. In non-superplastic conditions, deformation occurred under steady-state conditions without grain growth before significant flow localization whereas, under superplastic conditions, there was grain growth during the early stages of deformation, leading to strain hardening. The grains retained equiaxed shapes under all experimental conditions. Superplastic deformation is attributed to GBS, while non-superplastic deformation is attributed to intragranular dislocation creep with some contribution from GBS. The retention of equiaxed grain shapes during dislocation creep is consistent with a model based on local recovery related to the disturbance of triple junctions.

The Influence of Bilayer Composition on the Gel to Liquid Crystalline Transition

We report molecular dynamics simulations of bilayers using a united atom model with explicit solvent molecules. The bilayer consists of the single tail cationic surfactant behenyl trimethyl ammonium chloride (BTMAC) with stearyl alcohol (SA) as the cosurfactant. We study the gel to liquid crystalline transitions in the bilayer by varying the amount of water at fixed BTMAC to SA ratio as well as by varying the BTMAC to SA ratio at fixed water content. The bilayer is found to exist in the tilted, Lβ′ phase at low temperatures, and for the compositions investigated in this study, the Lβ′ to Lα melting transition occurred in the temperature range 330−338 K. For the highest BTMAC to SA composition (2:3 molar ratio), a diffuse headgroup−water interface is observed at lower temperatures, and an increase in the d-spacing occurs prior to the melting transition. This pretransition swelling is accompanied by a sharpening in the water density variation across the headgroup region of the bilayer. Signatures of this swelling effect which can be observed in the alkane density distributions, area per headgroup, and membrane thickness are attributed to the hydrophobic effect. At a fixed bilayer composition, the transition temperature (>338 K) from the Lβ′ to Lα transition obtained for the high water content bilayer (80 wt %) is similar to that obtained with low water content (54.3 wt %), confirming that the melting transition at these water contents is dominated by chain melting.

Design of a FIR filter for image restoration using principal component neural networks

The neural network finds its application in many image denoising applications because of its inherent characteristics such as nonlinear mapping and self-adaptiveness. The design of filters largely depends on the a-priori knowledge about the type of noise. Due to this, standard filters are application and image specific. Widely used filtering algorithms reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated general approach to design a finite impulse response filter based on principal component neural network (PCNN) is proposed in this study for image filtering, optimized in the sense of visual inspection and error metric. This algorithm exploits the inter-pixel correlation by iteratively updating the filter coefficients using PCNN. This algorithm performs optimal smoothing of the noisy image by preserving high and low frequency features. Evaluation results show that the proposed filter is robust under various noise distributions. Further, the number of unknown parameters is very few and most of these parameters are adaptively obtained from the processed image.

Use of finite wordlength FIR digital filter structures with improved magnitude and phase characteristics for reduction of muscle noise in EEG signals

One of the main disturbances in EEG signals is EMG artefacts generated by muscle movements. In the paper, the use of a linear phase FIR digital low-pass filter with finite wordlength precision coefficients is proposed, designed using the compensation procedure, to minimise EMG artefacts in contaminated EEG signals. To make the filtering more effective, different structures are used, i.e. cascading, twicing and sharpening (apart from simple low-pass filtering) of the designed FIR filter Modifications are proposed to twicing and sharpening structures to regain the linear phase characteristics that are lost in conventional twicing and sharpening operations. The efficacy of all these transformed filters in minimising EMG artefacts is studied, using SNR improvements as a performance measure for simulated signals. Time plots of the signals are also compared. Studies show that the modified sharpening structure is superior in performance to all other proposed methods. These algorithms have also been applied to real or recorded EMG-contaminated EEG signal. Comparison of time plots, and also the output SNR, show that the proposed modified sharpened structure works better in minimising EMG artefacts compared with other methods considered.

A DCT Based Filtering of Biomedical Images

Image filtering techniques have numerous potential applications in biomedical imaging and image processing. The design of filters largely depends on the a-priori knowledge about the type of noise corrupting the image and image features. This makes the standard filters to be application and image specific. The most popular filters such as average, Gaussian and Wiener reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated general approach to design filters based on discrete cosine transform (DCT) is proposed in this study for optimal medical image filtering. This algorithm exploits the better energy compaction property of DCT and re-arrange these coefficients in a wavelet manner to get the better energy clustering at desired spatial locations. This algorithm performs optimal smoothing of the noisy image by preserving high and low frequency features. Evaluation results show that the proposed filter is robust under various noise distributions.

Interface capturing simulations of acoustically driven bubble dynamics in and near tissue

Tissue injury during therapeutic ultrasound or lithotripsy is thought, in cases, to be due to the action of cavitation bubbles. Assessing this and mitigating it is challenging since bubble dynamics in the complex confinement of tissues or in small blood vessels are challenging to predict. Simulations tools require specialized algorithms to simultaneously represent strong acoustic waves and shocks, topologically complex liquid‐vapor phase boundaries, and the complex viscoelastic material dynamics of tissue. We discuss advances in a simulation tool for such situations. A single‐mesh Eulerian solver is used to solve the governing equations. Special sharpening terms maintain the liquid‐vapor interface in face of the finite numerical dissipation included in the scheme to accurately capture shocks. A recent enhancement to this formulation has significantly improved this interface capturing procedure, which is demonstrated for simulation of the Rayleigh collapse of a bubble. The solver also transports elastic stresses and can thus be used to assess the effects of elastic properties on bubble dynamics. A shock‐induced bubble collapse adjacent to a model elastic tissue is used to demonstrate this and draw some conclusions regarding the injury suppressing role that tissue elasticity might play.

Effects of different modes of hot cross-rolling in 7010 aluminum alloy: part I. evolution of microstructure and texture

The current study describes the evolution of microstructure and texture in an Al-Zn-Mg-Cu-Zr-based 7010 aluminum alloy during different modes of hot cross-rolling. Processing of materials involves three different types of cross-rolling. The development of texture in the one-step cross-rolled specimen can be described by a typical beta-fiber having the maximum intensity near Copper (Cu) component. However, for the multi-step cross-rolled specimens, the as-rolled texture is mainly characterized by a strong rotated-Brass (Bs) component and a very weak rotated-cube component. Subsequent heat treatment leads to sharpening of the major texture component (i.e., rotated-Bs). Furthermore, the main texture components in all the specimens appear to be significantly rotated in a complex manner away from their ideal positions because of non-symmetric deformations in the two rolling directions. Detailed microstructural study indicates that dynamic recovery is the dominant restoration mechanism operating during the hot rolling. During subsequent heat treatment, static recovery dominates, while a combination of particle-stimulated nucleation (PSN) and strain-induced grain boundary migration (SIBM) causes partial recrystallization of the grain structure. The aforementioned restoration mechanisms play an important role in the development of texture components. The textural development in the current study could be attributed to the combined effects of (a) cross-rolling and inter-pass annealing that reduce the intensity of Cu component after each successive pass, (b) recrystallization resistance of Bs-oriented grains, (c) stability of Bs texture under cross-rolling, and (d) Zener pinning by Al3Zr dispersoids.

A simple model for spatial disaggregation of evaporative fraction: Comparative study with thermal sharpened land surface temperature data over India

[1] Evaporative fraction (EF) is a measure of the amount of available energy at the earth surface that is partitioned into latent heat flux. The currently operational thermal sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) on satellite platforms provide data only at 1000 m, which constraints the spatial resolution of EF estimates. A simple model (disaggregation of evaporative fraction (DEFrac)) based on the observed relationship between EF and the normalized difference vegetation index is proposed to spatially disaggregate EF. The DEFrac model was tested with EF estimated from the triangle method using 113 clear sky data sets from the MODIS sensor aboard Terra and Aqua satellites. Validation was done using the data at four micrometeorological tower sites across varied agro-climatic zones possessing different land cover conditions in India using Bowen ratio energy balance method. The root-mean-square error (RMSE) of EF estimated at 1000 m resolution using the triangle method was 0.09 for all the four sites put together. The RMSE of DEFrac disaggregated EF was 0.09 for 250 m resolution. Two models of input disaggregation were also tried with thermal data sharpened using two thermal sharpening models DisTrad and TsHARP. The RMSE of disaggregated EF was 0.14 for both the input disaggregation models for 250 m resolution. Moreover, spatial analysis of disaggregation was performed using Landsat-7 (Enhanced Thematic Mapper) ETM+ data over four grids in India for contrasted seasons. It was observed that the DEFrac model performed better than the input disaggregation models under cropped conditions while they were marginally similar under non-cropped conditions.

Impact of Stone-Wales and lattice vacancy defects on the electro-thermal transport of the free standing structure of metallic ZGNR

We report the effect of topological as well as lattice vacancy defects on the electro-thermal transport properties of the metallic zigzag graphene nano ribbons at their ballistic limit. We employ the density function theory-Non equilibrium green's function combination to calculate the transmission details. We then present an elaborated study considering the variation in the electrical current and the heat current transport with the change in temperature as well as the voltage gradient across the nano ribbons. The comparative analysis shows, that in the case of topological defects, such as the Stone-Wales defect, the electrical current transport is minimum. Besides, for the voltage gradient of 0.5 Volt and the temperature gradient of 300 K, the heat current transport reduces by similar to 62 % and similar to 50% for the cases of Stones-Wales defect and lattice vacancy defect respectively, compared to that of the perfect one.

Disaggregation of LST over India: comparative analysis of different vegetation indices

The non-availability of high-spatial-resolution thermal data from satellites on a consistent basis led to the development of different models for sharpening coarse-spatial-resolution thermal data. Thermal sharpening models that are based on the relationship between land-surface temperature (LST) and a vegetation index (VI) such as the normalized difference vegetation index (NDVI) or fraction vegetation cover (FVC) have gained much attention due to their simplicity, physical basis, and operational capability. However, there are hardly any studies in the literature examining comprehensively various VIs apart from NDVI and FVC, which may be better suited for thermal sharpening over agricultural and natural landscapes. The aim of this study is to compare the relative performance of five different VIs, namely NDVI, FVC, the normalized difference water index (NDWI), soil adjusted vegetation index (SAVI), and modified soil adjusted vegetation index (MSAVI), for thermal sharpening using the DisTrad thermal sharpening model over agricultural and natural landscapes in India. Multi-temporal LST data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors obtained over two different agro-climatic grids in India were disaggregated from 960 m to 120 m spatial resolution. The sharpened LST was compared with the reference LST estimated from the Landsat data at 120 m spatial resolution. In addition to this, MODIS LST was disaggregated from 960 m to 480 m and compared with ground measurements at five sites in India. It was found that NDVI and FVC performed better only under wet conditions, whereas under drier conditions, the performance of NDWI was superior to other indices and produced accurate results. SAVI and MSAVI always produced poorer results compared with NDVI/FVC and NDWI for wet and dry cases, respectively.