High-Pressure High-Temperature Exploration of Phase Boundaries Using Raman Spectroscopy

Metastability of states can provide interesting properties that may not be readily accessible in a material’s ground state. Many materials show high levels of polymorphism, indicating a rich energy landscape and a potential for metastable states. Melt crystallization techniques provide a potential route to these states. We use a resistively heated diamond anvil cell (DAC) with fine control of a system’s pressure and temperature to explore these systems. Raman spectroscopy is used to track subtle structural changes across phase boundaries. Organic systems, such as glycine and aspirin, were our initial interest due to their high polymorphism and reported low melting temperatures; however, complications with these systems ultimately showed that they are not ideal candidates for this technique. Metallic systems with allowed Raman modes are better samples for this method. We successfully map the phase stability of β-tin under high pressure and temperature conditions using Raman spectroscopy

Visual-hint Boundary to Segment Algorithm for Image Segmentation

Image segmentation has been a very active research topic in image analysis area. Currently, most of the image segmentation algorithms are designed based on the idea that images are partitioned into a set of regions preserving homogeneous intra-regions and inhomogeneous inter-regions. However, human visual intuition does not always follow this pattern. A new image segmentation method named Visual-Hint Boundary to Segment (VHBS) is introduced, which is more consistent with human perceptions. VHBS abides by two visual hint rules based on human perceptions: (i) the global scale boundaries tend to be the real boundaries of the objects; (ii) two adjacent regions with quite different colors or textures tend to result in the real boundaries between them. It has been demonstrated by experiments that, compared with traditional image segmentation method, VHBS has better performance and also preserves higher computational efficiency.Comment: 45 page

Cavitation Inception - A Selective Review

This paper reviews recent developments in selected cavitation research areas which have been active mainly within the past two years. The new understanding resulting from this work is summarized. Research topics discussed are cavitation inception on smooth surfaces, on vortex cavitation and scaling, on the measurement of cavitation nuclei, and on the effects of polymer additives. Because of the selective nature of the review, a fairly comprehensive listing of recent contributions to the literature on these and related aspects of cavitation research is an essential part of the exposition

Automated visual tracking for studying the ontogeny of zebrafish swimming

The zebrafish Danio rerio is a widely used model organism in studies of genetics, developmental biology, and recently, biomechanics. In order to quantify changes in swimming during all stages of development, we have developed a visual tracking system that estimates the posture of fish. Our current approach assumes planar motion of the fish, given image sequences taken from a top view. An accurate geometric fish model is automatically designed and fit to the images at each time frame. Our approach works across a range of fish shapes and sizes and is therefore well suited for studying the ontogeny of fish swimming, while also being robust to common environmental occlusions. Our current analysis focuses on measuring the influence of vertebra development on the swimming capabilities of zebrafish. We examine wild-type zebrafish and mutants with stiff vertebrae (stocksteif) and quantify their body kinematics as a function of their development from larvae to adult (mutants made available by the Hubrecht laboratory, The Netherlands). By tracking the fish, we are able to measure the curvature and net acceleration along the body that result from the fish's body wave. Here, we demonstrate the capabilities of the tracking system for the escape response of wild-type zebrafish and stocksteif mutant zebrafish. The response was filmed with a digital high-speed camera at 1500 frames s–1. Our approach enables biomechanists and ethologists to process much larger datasets than possible at present. Our automated tracking scheme can therefore accelerate insight in the swimming behavior of many species of (developing) fish

A Modified Distortion Measurement Algorithm for Shape Coding

Efficient encoding of object boundaries has become increasingly prominent in areas such as content-based storage and retrieval, studio and television post-production facilities, mobile communications and other real-time multimedia applications. The way distortion between the actual and approximated shapes is measured however, has a major impact upon the quality of the shape coding algorithms. In existing shape coding methods, the distortion measure do not generate an actual distortion value, so this paper proposes a new distortion measure, called a modified distortion measure for shape coding (DMSC) which incorporates an actual perceptual distance. The performance of the Operational Rate Distortion optimal algorithm [1] incorporating DMSC has been empirically evaluated upon a number of different natural and synthetic arbitrary shapes. Both qualitative and quantitative results confirm the superior results in comparison with the ORD lgorithm for all test shapes, without any increase in computational complexity

Shapes From Pixels

Continuous-domain visual signals are usually captured as discrete (digital) images. This operation is not invertible in general, in the sense that the continuous-domain signal cannot be exactly reconstructed based on the discrete image, unless it satisfies certain constraints (\emph{e.g.}, bandlimitedness). In this paper, we study the problem of recovering shape images with smooth boundaries from a set of samples. Thus, the reconstructed image is constrained to regenerate the same samples (consistency), as well as forming a shape (bilevel) image. We initially formulate the reconstruction technique by minimizing the shape perimeter over the set of consistent binary shapes. Next, we relax the non-convex shape constraint to transform the problem into minimizing the total variation over consistent non-negative-valued images. We also introduce a requirement (called reducibility) that guarantees equivalence between the two problems. We illustrate that the reducibility property effectively sets a requirement on the minimum sampling density. One can draw analogy between the reducibility property and the so-called restricted isometry property (RIP) in compressed sensing which establishes the equivalence of the $\ell_0$ minimization with the relaxed $\ell_1$ minimization. We also evaluate the performance of the relaxed alternative in various numerical experiments.Comment: 13 pages, 14 figure

A CFD technique for estimating the flow distortion effects on LiDAR measurements when made in complex flow fields

The effect of flow distortion on the measurements produced by a LiDAR or SoDAR in close proximity to either complex terrain or a structure creating localised flow distortion is difficult to determine by analytical means. Also, as LiDARs and SoDARs are not point measurement devices, the techniques they employ for velocity measurements leads to complexities in the estimation of the effect of flow distortion on the accuracy of the measurements they make. This paper presents a method by which the effect of flow distortion on measurements made by a LiDAR in a distorted flow field may be determined using computational fluid dynamics. The results show that the error created by the flow distortion will cause the vector measured by a LiDAR to differ significantly from an equivalent point measurement. However, the results of the simulation show that, if the LiDAR is being used to measure the undisturbed flow field above a structure which creates highly localised flow distortion, the LiDAR results are less affected by the distortion of the local flow field than data acquired by a point measurement technique such as a cup anemometer

A robust lesion boundary segmentation algorithm using level set methods

This paper addresses the issue of accurate lesion segmentation in retinal imagery, using level set methods and a novel stopping mechanism - an elementary features scheme. Specifically, the curve propagation is guided by a gradient map built using a combination of histogram equalization and robust statistics. The stopping mechanism uses elementary features gathered as the curve deforms over time, and then using a lesionness measure, defined herein, ’looks back in time’ to find the point at which the curve best fits the real object. We compare the proposed method against five other segmentation algorithms performed on 50 randomly selected images of exudates with a database of clinician demarcated boundaries as ground truth