Interrelationship between Interphase Boundaries and Phase Contents near the Critical Compositions of Lead-Free Ferroelectric (Na0.5Bi0.5)TiO3-BaTiO3

Heterophase structures in lead-free perovskite-type ferroelectric solid solutions of (1 - z)(Na0.5Bi0.5)TiO3 - zBaTiO(3) are analysed for a few critical compositions near the morphotropic phase boundary (z = 0.05-0.07). Examples of the phase coexistence and elastic matching of the phases from different symmetry groups are considered to find optimum volume fractions of specific domain types and coexisting phases at the complete stress relief in two-phase samples. Some interrelations between these volume fractions are described using variants of the domain arrangement at changes in the composition and unit-cell parameters. The evaluated room-temperature volume fractions of the ferroelectric monoclinic (Cm symmetry) and tetragonal (P4mm symmetry) phases near the morphotropic phase boundary are in agreement with experimental data.

Macropores generated during shrinkage in two paddy soils using X-ray micro-computed tomography

Soil shrinkage curve represents a decrease of total porosity or an increase of bulk density with water loss. However, our knowledge of the dynamics of pores and their geometry during soil shrinkage is scarce, partially due to lack of reliable methods for determining soil pores in relation to change in soil water. This study aimed to investigate the dynamics of macropores (>30 mu m) of paddy soils during shrinkage. Two, paddy soils, which were sampled from one paddy field cultivated for 20 years (YPF) and the other one for over 100 years (OPF), represented difference in crack geometry in the field. Macropore parameters (volume, connectivity, and orientation of pores) and soil shrinkage parameters were determined on the same undisturbed soil cores by X-ray microtomography and shrinkage curve, respectively. Macroporosity was on average four times larger in the YPF than in the OPF whereas the shrinkage capacity was lower in the YPF as compared to the OPF (0.09 vs. 0.15 COLE). Soil shrinkage increased the volume of pores by 3.7% in the YPF and by 1.6% in the OPF as well as their connectivity. The formation of macropores occurred mostly in the proportional shrinkage phase. As a result, the slope of the proportional shrinkage phase was smaller in the YPF (0.65) than in the OPF (0.89). New macropores were cracks and extended pre-existing pores in the range of 225-1215 pm size without any preferential orientation. This work provides image evidences that in paddy soils with high shrinkage capacity more macropores are generated in the soil presenting a smaller proportional shrinkage slope. (C) 2015 Elsevier B.V. All rights reserved.

Framework for morphometric classification of cells in imaging flow cytometry

Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis. Lay description In this article, we propose a novel framework for processing the raw data generated using microfluidics based imaging flow cytometers. Microfluidics microscopy or microfluidics based imaging flow cytometry (mIFC) is a recent microscopy paradigm, that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy, which allows us imaging cells while they are in flow. In comparison to the conventional slide-based imaging systems, mIFC is a nascent technology enabling high throughput imaging of cells and is yet to take the form of a clinical diagnostic tool. The proposed framework process the raw data generated by the mIFC systems. The framework incorporates several steps: beginning from pre-processing of the raw video frames to enhance the contents of the cell, localising the cell by a novel, fully automatic, non-iterative graph based algorithm, extraction of different quantitative morphological parameters and subsequent classification of cells. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using cost-effective microfluidics based imaging flow cytometer. The cell lines of HL60, K562 and MOLT were obtained from ATCC (American Type Culture Collection) and are separately cultured in the lab. Thus, each culture contains cells from its own category alone and thereby provides the ground truth. Each cell is localised by finding a closed cell contour by defining a directed, weighted graph from the Canny edge images of the cell such that the closed contour lies along the shortest weighted path surrounding the centroid of the cell from a starting point on a good curve segment to an immediate endpoint. Once the cell is localised, morphological features reflecting size, shape and complexity of the cells are extracted and used to develop a support vector machine based classification system. We could classify the cell-lines with good accuracy and the results were quite consistent across different cross validation experiments. We hope that imaging flow cytometers equipped with the proposed framework for image processing would enable cost-effective, automated and reliable disease screening in over-loaded facilities, which cannot afford to hire skilled personnel in large numbers. Such platforms would potentially facilitate screening camps in low income group countries; thereby transforming the current health care paradigms by enabling rapid, automated diagnosis for diseases like cancer.