Finite size scaling in crossover among different random matrix ensembles in microscopic lattice models

Using numerical diagonalization we study the crossover among different random matrix ensembles (Poissonian, Gaussian orthogonal ensemble (GOE), Gaussian unitary ensemble (GUE) and Gaussian symplectic ensemble (GSE)) realized in two different microscopic models. The specific diagnostic tool used to study the crossovers is the level spacing distribution. The first model is a one-dimensional lattice model of interacting hard-core bosons (or equivalently spin 1/2 objects) and the other a higher dimensional model of non-interacting particles with disorder and spin-orbit coupling. We find that the perturbation causing the crossover among the different ensembles scales to zero with system size as a power law with an exponent that depends on the ensembles between which the crossover takes place. This exponent is independent of microscopic details of the perturbation. We also find that the crossover from the Poissonian ensemble to the other three is dominated by the Poissonian to GOE crossover which introduces level repulsion while the crossover from GOE to GUE or GOE to GSE associated with symmetry breaking introduces a subdominant contribution. We also conjecture that the exponent is dependent on whether the system contains interactions among the elementary degrees of freedom or not and is independent of the dimensionality of the system.

Raman Spectroscopic Studies on Screening of Myopathies

Myopathies are among the major causes of mortality in the world. There is no complete cure for this heterogeneous group of diseases, but a sensitive, specific, and fast diagnostic tool may improve therapy effectiveness. In this study, Raman spectroscopy is applied to discriminate between muscle mutants in Drosophila on the basis of associated changes at the molecular level. Raman spectra were collected from indirect flight muscles of mutants, upheld1 (up1), heldup(2) (hdp(2)), myosin heavy chain7 (Mhc7), actin88F(KM88) (Act88F(KM88)), upheld101 (up101), and Canton-S (CS) control group, for both 2 and 12 days old flies. Difference spectra (mutant minus control) of all the mutants showed an increase in nucleic acid and beta-sheet and/or random coil protein content along with a decrease in a-helix protein. Interestingly, the 12th day samples of up1 and Act88F(KM88) showed significantly higher levels of glycogen and carotenoids than CS. A principal components based linear discriminant analysis classification model was developed based on multidimensional Raman spectra, which classified the mutants according to their pathophysiology and yielded an overall accuracy of 97% and 93% for 2 and 12 days old flies, respectively. The up1 and Act88F(KM88) (nemaline-myopathy) mutants form a group that is clearly separated in a linear discriminant plane from up101 and hdp2 (cardiomyopathy) mutants. Notably, Raman spectra from a human sample with nemaline-myopathy formed a cluster with the corresponding Drosophila mutant (up1). In conclusion, this is the first demonstration in which myopathies, despite their heterogeneity, were screened on the basis of biochemical differences using Raman spectroscopy.

Deformability Measurement of Single-Cells at High-Throughput With Imaging Flow Cytometry

Disease conditions like malaria, sickle cell anemia, diabetes mellitus, cancer, etc., are known to significantly alter the deformability of certain types of cells (red blood cells, white blood cells, circulating tumor cells, etc.). To determine the cellular deformability, techniques like micropipette aspiration, atomic force microscopy, optical tweezers, quantitative phase imaging have been developed. Many of these techniques have an advantage of determining the single cell deformability with ultrahigh precision. However, the suitability of these techniques for the realization of a deformability based diagnostic tool is questionable as they are expensive and extremely slow to operate on a huge population of cells. In this paper, we propose a technique for high-throughput (800 cells/s) determination of cellular deformability on a single cell basis. This technique involves capturing the image(s) of cells in flow that have undergone deformation under the influence of shear gradient generated by the fluid flowing through the microfluidic channels. Deformability indices of these cells can be computed by performing morphological operations on these images. We demonstrate the applicability of this technique for examining the deformability index on healthy, diabetic, and sphered red blood cells. We believe that this technique has a strong role to play in the realization of a potential tool that uses deformability as one of the important criteria in disease diagnosis.

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.

An Evaluation of Inventory Management and Performance in Indian Machine Tool SMEs: An Exploratory Study

Inventory Management (IM) plays a decisive role in the enhancement of efficiency and competitiveness of manufacturing enterprises. Therefore, major manufacturing enterprises are following IM practices as a strategy to improve efficiency and achieve competitiveness. However, the spread of IM culture among Small and Medium Enterprises (SMEs) is limited due to lack of initiation, expertise and financial limitations in developed countries, leave alone developing countries. With this backdrop, this paper makes an attempt to ascertain the role and importance of IM practices and performance of SMEs in the machine tools industry of Bangalore, India. The relationship between inventory management practices and inventory cost are probed based on primary data gathered from 91 SMEs. The paper brings out that formal IM practices have a positive impact on the inventory performance of SMEs.

Defect-selective photothermal imaging: a sensitive tool for damage mapping in optical coatings

A defect-selective photothermal imaging system for the diagnostics of optical coatings is demonstrated. The instrument has been optimized for pump and probe parameters, detector performance, and signal processing algorithm. The imager is capable of mapping purely optical or thermal defects efficiently in coatings of low damage threshold and low absorbance. Detailed mapping of minor inhomogeneities at low pump power has been achieved through the simultaneous action of a low-noise fiber optic photothermal beam defection sensor and a common-mode-rejection demodulation (CMRD) technique. The linearity and sensitivity of the sensor have been examined theoretically and experimentally, and the signal to noise ratio improvement factor is found to be about 110 compared to a conventional bicell photodiode. The scanner is so designed that mapping of static or shock sensitive samples is possible. In the case of a sample with absolute absorptance of 3.8 x 10(-4), a change in absorptance of about 0.005 x 10(-4) has been detected without ambiguity, ensuring a contrast parameter of 760. This is about 1085% improvement over the conventional approach containing a bicell photodiode, at the same pump power. The merits of the system have been demonstrated by mapping two intentionally created damage sites in a MgF2 coating on fused silica at different excitation powers. Amplitude and phase maps were recorded for thermally thin and thick cases, and the results are compared to demonstrate a case which, in conventional imaging, would lead to a deceptive conclusion regarding the type and location of the damage. Also, a residual damage profile created by long term irradiation with high pump power density has been depicted.

A Case of Simple Tool Use in Wild Liontailed Macaques (Macaca silenus)

Three members of a group of liontailed macaques (Macaea silenus) were seen to use leaves for food preparation. Other examples of prey-selection and hunting behaviour in liontailed macaques reflect individual- and group-specific skills. The absence of similar patterns in bonnet macaques (Macaca radiata) living in the same habitat might be related to differences in the social design and indicate the high significance of social aspects for the occurrence and manifestation of innovative behaviour.

Inventory Management Performance in Indian Machine Tool SMEs: What factors do influence them

These instructions give on basic guidelines for preparing papers for the IEEM 2008 Proceedings. Inventory Management (IM) plays a decisive role in the enhancement of efficiency for manufacturing enterprise competitiveness. Therefore, major manufacturing industries are following inventory management practices as a strategy to improve efficiency and achieve competitiveness. However, the spread of inventory management culture among Small and Medium Enterprises (SMEs) is limited due to lack of initiation, expertise and financial limitations in developed countries, leave alone developing countries.With this backdrop, this paper makes an attempt to ascertain the factors which influence the IM performance of SMEs in the machine tools industry of Bangalore, India. This issue is probed based on primary data gathered from 91 SMEs. The paper brings out that two sets of factors namely organizational support and external pressure have a positive impact on the inventory performance of SMEs.

Mathematical model and rule extraction for tool wear monitoring problem using nature inspired techniques

In this paper, pattern classification problem in tool wear monitoring is solved using nature inspired techniques such as Genetic Programming(GP) and Ant-Miner (AM). The main advantage of GP and AM is their ability to learn the underlying data relationships and express them in the form of mathematical equation or simple rules. The extraction of knowledge from the training data set using GP and AM are in the form of Genetic Programming Classifier Expression (GPCE) and rules respectively. The GPCE and AM extracted rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in GP evolved GPCE and AM based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The performance of the data classification using GP and AM is as good as the classification accuracy obtained in the earlier study.

Structure-Based Phylogeny as a Diagnostic for Functional Characterization of Proteins with a Cupin Fold

Background: The members of cupin superfamily exhibit large variations in their sequences, functions, organization of domains, quaternary associations and the nature of bound metal ion, despite having a conserved beta-barrel structural scaffold. Here, an attempt has been made to understand structure-function relationships among the members of this diverse superfamily and identify the principles governing functional diversity. The cupin superfamily also contains proteins for which the structures are available through world-wide structural genomics initiatives but characterized as ``hypothetical''. We have explored the feasibility of obtaining clues to functions of such proteins by means of comparative analysis with cupins of known structure and function. Methodology/Principal Findings: A 3-D structure-based phylogenetic approach was undertaken. Interestingly, a dendrogram generated solely on the basis of structural dissimilarity measure at the level of domain folds was found to cluster functionally similar members. This clustering also reflects an independent evolution of the two domains in bicupins. Close examination of structural superposition of members across various functional clusters reveals structural variations in regions that not only form the active site pocket but are also involved in interaction with another domain in the same polypeptide or in the oligomer. Conclusions/Significance: Structure-based phylogeny of cupins can influence identification of functions of proteins of yet unknown function with cupin fold. This approach can be extended to other proteins with a common fold that show high evolutionary divergence. This approach is expected to have an influence on the function annotation in structural genomics initiatives.

EIT as a tool to observe dual wavelength operation of a semiconductor laser

We propose a simplified technique for dual wavelength operation of an extended cavity semiconductor laser, and its characterization using electromagnetically induced transparency (EIT). In this laser cavity scheme light beam is made converging before it incidences on the cavity grating. The converging angle of the beam creates two longitudinal oscillating modes of resonating cavity. Frequency separation between the longitudinal modes are measured with the help of beat frequency generation in a photodiode and creating pair of EIT spectra in Rb vapor. The pair of EIT dips that are generated due to dual wavelength of this laser (that is used as control laser) can be used to estimate frequency difference between the generated wavelengths. Width of EIT spectra can be used to estimate line width of individual wavelength components.

Fluorescence polarization as a tool to study lectin-sugar interaction. An investigation of the binding of 4-methylumbelliferyl beta-D-galactopyranoside to Abrus precatorious agglutinin

Polarization of ligand fluorescence was used to study the binding of 4-methylumbelliferyl beta-D-galactopyranoside (MeUmb-Galp) to Abrus precatorious agglutinin. The binding of the fluorescent sugar to the lectin led to considerable polarization of the MeUmb-Galp fluorescence, which was also quenched by about 30% on binding to the lectin. The binding of the fluorescent sugar was carbohydrate-specific, as evidenced by inhibition of both fluorescence polarization and quenching when lectin was preincubated with lactose. The association constant as determined by fluorescence polarization is 1.42 x 10(4) M-1 at 25 degrees C and is in excellent agreement with those determined by fluorescence quenching (Ka = 1.51 x 10(4) M-1) and equilibrium dialysis (Ka = 1.62 x 10(4) M-1) at 25 degrees C. The numbers of binding sites as determined by fluorescence polarization, quenching and equilibrium dialysis agree very well with one another, n being equal to 2.0 +/- 0.05. The consistency between the association constant value determined by fluorescence polarization, quenching and equilibrium dialysis shows the validity of this approach to study lectin-sugar interaction.

Influence of tool rake angle on the quality of pure magnesium chip-consolidated product

Chips were produced by orthogonal Cutting of cast pure magnesium billet with three different tool rake angles viz., -15 degrees, -5 degrees and +15 degrees on a lathe. Chip consolidation by solid state recycling technique involved cold compaction followed by hot extrusion. The extruded products were characterized for microstructure and mechanical properties. Chip-consolidated products from -15 degrees rake angle tools showed 19% increase in tensile strength, 60% reduction ingrain size and 12% increase in hardness compared to +15 degrees rake chip-consolidated product indicating better chip bonding and grain refinement. Microstructure of the fracture specimen Supports the abovefinding. On the overall, the present work high lights the importance of tool take angle in determining the quality of the chip-consolidated products. (C) 2009 Elsevier B.V. All rights reserved.

COMPASS – A tool for evaluation of compression strategies for embedded processors

A major concern of embedded system architects is the design for low power. We address one aspect of the problem in this paper, namely the effect of executable code compression. There are two benefits of code compression – firstly, a reduction in the memory footprint of embedded software, and secondly, potential reduction in memory bus traffic and power consumption. Since decompression has to be performed at run time it is achieved by hardware. We describe a tool called COMPASS which can evaluate a range of strategies for any given set of benchmarks and display compression ratios. Also, given an execution trace, it can compute the effect on bus toggles, and cache misses for a range of compression strategies. The tool is interactive and allows the user to vary a set of parameters, and observe their effect on performance. We describe an implementation of the tool and demonstrate its effectiveness. To the best of our knowledge this is the first tool proposed for such a purpose.

Seismic Microzonation: A Tool for Disaster Mitigation Planning

Seismic microzonation has generally been recognized as the most accepted tool in seismic hazard assessment and risk evaluation. In general, risk reduction can be done by reducing the hazard, the vulnerability or the value at risk. Since the earthquake hazard can not be reduced, one has to concentrate on vulnerability and value at risk. The vulnerability of an urban area / municipalities depends on the vulnerability of infrastructure and redundancies within the infrastructure. The earthquake risk is the damage to buildings along with number of people that are killed / hurt and the economic losses during the event due to an earthquake with a return period corresponding to this time period. The principal approaches one can follow to reduce these losses are to avoid, if possible, high hazard areas for the siting of buildings and infrastructure, and further ensure that the buildings and infrastructure are designed and constructed to resist expected earthquake loads. This can be done if one can assess the hazard at local scales. Seismic microzonation maps provide the basis for scientifically based decision-making to reduce earthquake risk for Govt./public agencies, private owners and the general public. Further, seismic microzonation carried out on an appropriate scale provides a valuable tool for disaster mitigation planning and emergency response planning for urban centers / municipalities. It provides the basis for the identification of the areas of the city / municipality which are most likely to experience serious damage in the event of an earthquake.