On the critical thickness for non-localized to localized plastic flow transition in metallic glasses: A molecular dynamics study

Molecular dynamics simulations were employed to investigate the specimen thickness-dependent tensile behavior of a series of Cu(x)Z(100-x) (x = 20, 40, 50, 64 and 80 at%) metallic glass (MG) films, with a particular focus on the critical thickness, tc, below which non-localized plastic flow takes place. The simulation results reveal that while the transition occurs in all the alloys examined, t(c) is sensitive to the composition. We rationalize t(c) by postulating that the strain energy stored in the sample at the onset of plastic deformation has to be sufficient for the formation of shear bands. The composition-dependence of t(c) was found to correlate with the average activation energy of the atomic level plastic deformation events. (C) 2015 Elsevier Ltd. All rights reserved.

Localized Excitations and the Morphology of Cooperatively Rearranging Regions in a Colloidal Glass-Forming Liquid

We develop a scheme based on a real space microscopic analysis of particle dynamics to ascertain the relevance of dynamical facilitation as a mechanism of structural relaxation in glass-forming liquids. By analyzing the spatial organization of localized excitations within clusters of mobile particles in a colloidal glass former and examining their partitioning into shell-like and corelike regions, we establish the existence of a crossover from a facilitation-dominated regime at low area fractions to a collective activated hopping-dominated one close to the glass transition. This crossover occurs in the vicinity of the area fraction at which the peak of the mobility transfer function exhibits a maximum and the morphology of cooperatively rearranging regions changes from stringlike to a compact form. Collectively, our findings suggest that dynamical facilitation is dominated by collective hopping close to the glass transition, thereby constituting a crucial step towards identifying the correct theoretical scenario for glass formation.

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.

Localized Charge Carrier Transport Properties of Zn1-x Ni (x) O/NiO Two-Phase Composites

We report the localized charge carrier transport of two-phase composite Zn1-x Ni (x) O/NiO (0 a parts per thousand currency sign x a parts per thousand currency sign 1) using the temperature dependence of ac-resistivity rho (ac)(T) across the N,el temperature T (N) (= 523 K) of nickel oxide. Our results provide strong evidence to the variable range hopping of charge carriers between the localized states through a mechanism involving spin-dependent activation energies. The temperature variation of carrier hopping energy epsilon (h)(T) and nearest-neighbor exchange-coupling parameter J (ij)(T) evaluated from the small poleron model exhibits a well-defined anomaly across T (N). For all the composite systems, the average exchange-coupling parameter (J (ij))(AVG) nearly equals to 70 meV which is slightly greater than the 60-meV exciton binding energy of pure zinc oxide. The magnitudes of epsilon (h) (similar to 0.17 eV) and J (ij) (similar to 11 meV) of pure NiO synthesized under oxygen-rich conditions are consistent with the previously reported theoretical estimation based on Green's function analysis. A systematic correlation between the oxygen stoichiometry and, epsilon (h)(T) and J (ij)(T) is discussed.

Integrals of motion for one-dimensional Anderson localized systems

Anderson localization is known to be inevitable in one-dimension for generic disordered models. Since localization leads to Poissonian energy level statistics, we ask if localized systems possess `additional' integrals of motion as well, so as to enhance the analogy with quantum integrable systems. We answer this in the affirmative in the present work. We construct a set of nontrivial integrals of motion for Anderson localized models, in terms of the original creation and annihilation operators. These are found as a power series in the hopping parameter. The recently found Type-1 Hamiltonians, which are known to be quantum integrable in a precise sense, motivate our construction. We note that these models can be viewed as disordered electron models with infinite-range hopping, where a similar series truncates at the linear order. We show that despite the infinite range hopping, all states but one are localized. We also study the conservation laws for the disorder free Aubry-Andre model, where the states are either localized or extended, depending on the strength of a coupling constant. We formulate a specific procedure for averaging over disorder, in order to examine the convergence of the power series. Using this procedure in the Aubry-Andre model, we show that integrals of motion given by our construction are well-defined in localized phase, but not so in the extended phase. Finally, we also obtain the integrals of motion for a model with interactions to lowest order in the interaction.

Localized Solid-State Amorphization at Grain Boundaries in a Nanocrystalline Al Solid Solution Subjected to Surface Mechanical Attrition

Using high-resolution electron microscopy, localized solid-state amorphization (SSA) was observed in a nanocrystalline (NC) Al solid solution (weight per cent 4.2 Cu, 0.3 Mn, the rest being Al) subjected to a surface mechanical attrition treatment. It was found that the deformation-induced SSA may occur at the grain boundary (GB) where either the high density dislocations or dislocation complexes are present. It is suggested that lattice instability due to elastic distortion within the dislocation core region plays a significant role in the initiation of the localized SSA at defective sites. Meanwhile, the GB of severely deformed NC grains exhibits a continuously varying atomic structure in such a way that while most of the GB is ordered but reveals corrugated configurations, localized amorphization may occur along the same GB.

Simulating dynamic covariance structures for testing the adaptive behavior of variable selection algorithms (Invited Paper)

Variable selection for regression is a classical statistical problem, motivated by concerns that too large a number of covariates may bring about overfitting and unnecessarily high measurement costs. Novel difficulties arise in streaming contexts, where the correlation structure of the process may be drifting, in which case it must be constantly tracked so that selections may be revised accordingly. A particularly interesting phenomenon is that non-selected covariates become missing variables, inducing bias on subsequent decisions. This raises an intricate exploration-exploitation tradeoff, whose dependence on the covariance tracking algorithm and the choice of variable selection scheme is too complex to be dealt with analytically. We hence capitalise on the strength of simulations to explore this problem, taking the opportunity to tackle the difficult task of simulating dynamic correlation structures. © 2008 IEEE.

Models and algorithms for detection and tracking of coordinated groups

In this paper, we describe models and algorithms for detection and tracking of group and individual targets. We develop two novel group dynamical models, within a continuous time setting, that aim to mimic behavioural properties of groups. We also describe two possible ways of modeling interactions between closely using Markov Random Field (MRF) and repulsive forces. These can be combined together with a group structure transition model to create realistic evolving group models. We use a Markov Chain Monte Carlo (MCMC)-Particles Algorithm to perform sequential inference. Computer simulations demonstrate the ability of the algorithm to detect and track targets within groups, as well as infer the correct group structure over time. ©2008 IEEE.

Models and algorithms for tracking of maneuvering objects using variable rate particle filters

Standard algorithms in tracking and other state-space models assume identical and synchronous sampling rates for the state and measurement processes. However, real trajectories of objects are typically characterized by prolonged smooth sections, with sharp, but infrequent, changes. Thus, a more parsimonious representation of a target trajectory may be obtained by direct modeling of maneuver times in the state process, independently from the observation times. This is achieved by assuming the state arrival times to follow a random process, typically specified as Markovian, so that state points may be allocated along the trajectory according to the degree of variation observed. The resulting variable dimension state inference problem is solved by developing an efficient variable rate particle filtering algorithm to recursively update the posterior distribution of the state sequence as new data becomes available. The methodology is quite general and can be applied across many models where dynamic model uncertainty occurs on-line. Specific models are proposed for the dynamics of a moving object under internal forcing, expressed in terms of the intrinsic dynamics of the object. The performance of the algorithms with these dynamical models is demonstrated on several challenging maneuvering target tracking problems in clutter. © 2006 IEEE.

On the transition from displacement to mixing ventilation with a localized heat source

We investigate the steady state natural ventilation of a room heated at the base and consisting of two vents at different levels. We explore how the air flow rate and internal temperature relative to the exterior vary as a function of the vent areas, position of the vents and heat load in order to establish appropriate ventilation strategies for a room. When the room is heated by a distributed source, the room becomes well mixed and the steady state ventilation rate depends on the heating rate, the area of the vents and the distance between the lower and upper level vents. However, when the room is heated by a localised source the room becomes stratified. If the effective ventilation area is sufficiently large, then the interface separating the two layers lies above the inlet vent and the lower layer is comprised of ambient fluid. In this case the upper layer is warmer than in the well mixed case and the ventilation rate is smaller. However, if the effective area for ventilation is sufficiently small, then the interface separating the two layers lies below the inlet vent and the lower layer is comprised of warm fluid which originates as the cold incoming fluid mixes during descent from the vent through the upper layer. In this case both the ventilation rate and the upper layer temperature are the same as in the case of a distributed heat load. As the vertical separation between lower and upper level vents decreases, then the temperature difference between the layers falls to zero and the room becomes approximately well mixed. These findings suggest how the appropriate ventilation strategy for a room can be varied depending on the exterior temperature, with mixing ventilation more suitable for winter conditions and displacement ventilation for warmer external temperatures.

Effects of mechanical and electrical coupling on the parametric sensitivity of mode localized sensors

We compare and contrast the effects of two distinctly different mechanisms of coupling (mechanical and electrical) on the parametric sensitivity of micromechanical sensors utilizing mode localization for sensor applications. For the first time, the strong correlation between mode localization and the phenomenon of 'eigenvalue loci-veering' is exploited for accurate quantification of the strength of internal coupling in mode localized sensors. The effects of capacitive coupling-spring tuning on the parametric sensitivity of electrically coupled resonators utilizing this sensing paradigm is also investigated and a mass sensor with sensitivity tunable by over 400% is realized. ©2009 IEEE.