@article {20548, title = {Rapid, quantitative therapeutic screening for Alzheimer{\textquoteright}s enzymes enabled by optimal signal transduction with transistors}, journal = {The Analyst}, volume = {145}, year = {2020}, month = {Feb-04-2021}, pages = {2925 - 2936}, issn = {0003-2654}, doi = {10.1039/C9AN01804B}, url = {http://xlink.rsc.org/?DOI=C9AN01804Bhttp://pubs.rsc.org/en/content/articlepdf/2020/AN/C9AN01804Bhttp://pubs.rsc.org/en/content/articlepdf/2020/AN/C9AN01804B}, author = {Le, Son T. and Morris, Michelle A. and Cardone, Antonio and Guros, Nicholas B. and Klauda, Jeffery B. and Sperling, Brent A. and Richter, Curt A. and Pant, Harish C. and Balijepalli, Arvind} } @article {20449, title = {Quantum Capacitance-Limited MoS2 Biosensors Enable Remote Label-Free Enzyme Measurements}, journal = {Nanoscale}, year = {2019}, month = {Jan-01-2019}, issn = {2040-3364}, doi = {10.1039/C9NR03171E}, url = {http://pubs.rsc.org/en/Content/ArticleLanding/2019/NR/C9NR03171Ehttp://pubs.rsc.org/en/content/articlepdf/2019/NR/C9NR03171E}, author = {Le, Son T and Guros, Nicholas B and Bruce, Robert C and Cardone, Antonio and Amin, Niranjana D and Zhang, Siyuan and Klauda, Jeffery and Pant, Harish C and Richter, Curt A and Balijepalli, Arvind} } @article {20252, title = {Deep-learning-assisted Volume Visualization}, journal = {IEEE Transactions on Visualization and Computer Graphics}, year = {2018}, month = {Jan-01-2018}, pages = {1 - 1}, issn = {1077-2626}, doi = {10.1109/TVCG.2018.2796085}, url = {http://ieeexplore.ieee.org/document/8265023/http://xplorestaging.ieee.org/ielx7/2945/4359476/08265023.pdf?arnumber=8265023}, author = {Cheng, Hsueh-Chien and Cardone, Antonio and Jain, Somay and Krokos, Eric and Narayan, Kedar and Subramaniam, Sriram and Varshney, Amitabh} } @conference {20251, title = {Interpolation-Based Gray-Level Co-Occurrence Matrix Computation for Texture Directionality Estimation}, booktitle = {IEEE 22nd Signal Processing Algorithms, Architectures, Arrangements, and Applications Conference}, year = {2018}, month = {12/06/2018}, publisher = {IEEE}, organization = {IEEE}, address = {Poznan, Poland}, abstract = {A novel interpolation-based model for the computation of the Gray Level Co-occurrence Matrix (GLCM) is presented. The model enables GLCM computation for any real valued angles and offsets, as opposed to the traditional, lattice-based model. A texture directionality estimation algorithm is defined using the GLCM-derived correlation feature. The robustness of the algorithm with respect to image blur and additive Gaussian noise is evaluated. It is concluded that directionality estimation is robust to image blur and low noise levels. For high noise levels, the mean error increases but remains bounded. The performance of the directionality estimation algorithm is illustrated on fluorescence microscopy images of fibroblast cells. The algorithm was implemented in C++ and the source code is available in an openly accessible repository.}, isbn = { 978-8-3620-6533-2}, doi = {10.23919/SPA.2018.8563413 }, url = {https://ieeexplore.ieee.org/document/8563413}, author = {Marcin Kociolek and Mary Brady and Peter Bajcsy and Cardone, Antonio} } @article {20448, title = {A Bioinformatics 3D Cellular Morphotyping Strategy for Assessing Biomaterial Scaffold Niches}, journal = {ACS Biomaterials Science \& Engineering}, volume = {3}, year = {2017}, month = {Sep-10-2017}, pages = {2302 - 2313}, issn = {2373-9878}, doi = {10.1021/acsbiomaterials.7b00473}, url = {http://pubs.acs.org/doi/10.1021/acsbiomaterials.7b00473http://pubs.acs.org/doi/pdf/10.1021/acsbiomaterials.7b00473}, author = {Florczyk, Stephen J. and Simon, Mylene and Juba, Derek and Pine, P. Scott and Sarkar, Sumona and Chen, Desu and Baker, Paula J. and Bodhak, Subhadip and Cardone, Antonio and Brady, Mary C. and Bajcsy, Peter and Simon, Carl G.} } @proceedings {20156, title = {Deep-learning-assisted visualization for live-cell images}, year = {2017}, month = {09/2017}, publisher = {IEEE}, address = {Beijing, China}, abstract = {Analyzing live-cell images is particularly challenging because cells move at the same time they undergo systematic changes. Visually inspecting live-cell images therefore involves simultaneously tracking individual cells and detecting relevant spatio-temporal changes. The high cognitive burden of such a complex task makes this kind of analysis inefficient and error-prone. In this paper we describe a deep-learning-assisted visualization based on automatically derived high-level features to identify target cell changes in live-cell images. Applying a novel user-mediated color assignment scheme that maps abstract features into corresponding colors, we create color-based visual annotations that facilitate visual reasoning and analysis of complex time varying live-cell imagery datasets. The visual representations can be used to study temporal changes in cells, such as the morphological changes in cell at various stages of life cycle.}, keywords = {deep learning, live-cell images, Visualization}, author = {Hsueh-Chien Cheng and Cardone, Antonio and Krokos, Eric and Stoica, Bogdan and Faden, Alan and Varshney, Amitabh} } @conference {20155, title = {Interactive exploration of microstructural features in gigapixel microscopy images}, booktitle = {IEEE International Conference on Image Processing}, year = {2017}, month = {09/2017}, publisher = {IEEE}, organization = {IEEE}, address = {Beijing, China}, abstract = {Modern imaging technologies enable the study of microstructural features, which require capturing the finest details in high-resolution gigapixel images. Nevertheless, the resolution disparity between gigapixel images and megapixel displays presents a challenge to effective visual analysis because subtle texture differences are hardly perceivable at coarser resolutions. In this paper we present a hierarchical segmentation technique based on joint distribution of intensity and noise-resistant local binary patterns to differentiate subtle microstructural textures across various scales. The coarse-to-fine segmentation procedure subdivides each parent segment into texturally-distinct child segments at progressively higher resolutions. The hierarchical structure of segments allows creating intermediate segmentation results interactively. Based on the intermediate results, we highlight regions with texture differences using distinct colors, which provide salient visual hints to users despite of the current viewing resolution. Our new technique has been validated on large microscopy images and shows promising results.}, keywords = {gigapixel images, Image segmentation}, author = {Hsueh-Chien Cheng and Cardone, Antonio and Varshney, Amitabh} } @conference {20065, title = {3D Cellular Morphotyping of Scaffold Niches}, booktitle = {2016 32nd Southern Biomedical Engineering Conference (SBEC)}, year = {2016}, publisher = {IEEE}, organization = {IEEE}, author = {Florczyk, Stephen J and Simon, Mylene and Juba, Derek and Pine, P Scott and Sarkar, Sumona and Chen, Desu and Baker, Paula J and Bodhak, Subhadip and Cardone, Antonio and Brady, Mary and others} } @article {20060, title = {Computational study of the inhibitory mechanism of~the kinase CDK5 hyperactivity by peptide p5 and derivation of a pharmacophore}, journal = {Journal of Computer-Aided Molecular Design}, volume = {30}, year = {2016}, month = {Jan-06-2016}, pages = {513 - 521}, issn = {0920-654X}, doi = {10.1007/s10822-016-9922-3}, url = {http://link.springer.com/10.1007/s10822-016-9922-3http://link.springer.com/content/pdf/10.1007/s10822-016-9922-3http://link.springer.com/content/pdf/10.1007/s10822-016-9922-3.pdfhttp://link.springer.com/article/10.1007/s10822-016-9922-3/fulltext.html}, author = {Cardone, Antonio and Brady, M. and Sriram, R. and Pant, H. C. and Hassan, S. A.} } @article {19903, title = {Detection and characterization of nonspecific, sparsely populated binding modes in the early stages of complexation.}, journal = {J Comput Chem}, year = {2015}, month = {2015 Mar 18}, abstract = {

A method is proposed to study protein-ligand binding in a system governed by specific and nonspecific interactions. Strong associations lead to narrow distributions in the proteins configuration space; weak and ultraweak associations lead instead to broader distributions, a manifestation of nonspecific, sparsely populated binding modes with multiple interfaces. The method is based on the notion that a discrete set of preferential first-encounter modes are metastable states from which stable (prerelaxation) complexes at equilibrium evolve. The method can be used to explore alternative pathways of complexation with statistical significance and can be integrated into a general algorithm to study protein interaction networks. The method is applied to a peptide-protein complex. The peptide adopts several low-population conformers and binds in a variety of modes with a broad range of affinities. The system is thus well suited to analyze general features of binding, including conformational selection, multiplicity of binding modes, and nonspecific interactions, and to illustrate how the method can be applied to study these problems systematically. The equilibrium distributions can be used to generate biasing functions for simulations of multiprotein systems from which bulk thermodynamic quantities can be calculated. {\textcopyright} 2015 Wiley Periodicals, Inc.

}, issn = {1096-987X}, doi = {10.1002/jcc.23883}, author = {Cardone, Antonio and Bornstein, Aaron and Pant, Harish C and Brady, Mary and Sriram, Ram and Hassan, Sergio A} } @conference {20066, title = {Estimating Actin Fiber Orientation using Interpolation-Based Grey-Level Co-Occurrence Matrix Computation}, booktitle = {BioImage Informatics Conference }, year = {2015}, month = {10/2015}, author = {Cardone, Antonio and Brady, Mary and Kociolek, Marcin and Bajcsy, Peter} } @conference {20067, title = {Segmentation and sub-cellular feature-based analysis of microscopy images}, booktitle = {BioImage Informatics Conference }, year = {2015}, month = {10/2015}, author = {Cardone, Antonio and Chalfoun, Joe and Peskin, Adele and Bajcsy, Peter and Kociolek, Marcin and Bhadriraju, Kiran and Brady, Mary} } @article {20062, title = {Survey statistics of automated segmentations applied to optical imaging of mammalian cells}, journal = {BMC bioinformatics}, volume = {16}, year = {2015}, pages = {1}, author = {Bajcsy, Peter and Cardone, Antonio and Chalfoun, Joe and Halter, Michael and Juba, Derek and Kociolek, Marcin and Majurski, Michael and Peskin, Adele and Simon, Carl and Simon, Mylene and others} } @article {19372, title = {Parallel geometric classification of stem cells by their three-dimensional morphology}, journal = {Computational Science \& Discovery}, volume = {6}, year = {2013}, month = {01/2013}, pages = {015007}, doi = {10.1088/1749-4699/6/1/015007}, author = {Juba,Derek and Cardone, Antonio and Ip, Cheuk Yiu and Simon Jr, Carl G and K Tison, Christopher and Kumar, Girish and Brady,Mary and Varshney, Amitabh} } @article {19371, title = {Segmenting time-lapse phase contrast images of adjacent NIH 3T3 cells.}, journal = {Journal of microscopy}, volume = {249}, year = {2013}, month = {2013 Jan}, pages = {41-52}, abstract = {We present a new method for segmenting phase contrast images of NIH 3T3 fibroblast cells that is accurate even when cells are physically in contact with each other. The problem of segmentation, when cells are in contact, poses a challenge to the accurate automation of cell counting, tracking and lineage modelling in cell biology. The segmentation method presented in this paper consists of (1) background reconstruction to obtain noise-free foreground pixels and (2) incorporation of biological insight about dividing and nondividing cells into the segmentation process to achieve reliable separation of foreground pixels defined as pixels associated with individual cells. The segmentation results for a time-lapse image stack were compared against 238 manually segmented images (8219 cells) provided by experts, which we consider as reference data. We chose two metrics to measure the accuracy of segmentation: the {\textquoteright}Adjusted Rand Index{\textquoteright} which compares similarities at a pixel level between masks resulting from manual and automated segmentation, and the {\textquoteright}Number of Cells per Field{\textquoteright} (NCF) which compares the number of cells identified in the field by manual versus automated analysis. Our results show that the automated segmentation compared to manual segmentation has an average adjusted rand index of 0.96 (1 being a perfect match), with a standard deviation of 0.03, and an average difference of the two numbers of cells per field equal to 5.39\% with a standard deviation of 4.6\%.}, keywords = {Animals, Cell Adhesion, Cell Count, Cell Division, Cell Shape, Computational Biology, Fibroblasts, Image Processing, Computer-Assisted, Mice, Microscopy, Phase-Contrast, NIH 3T3 Cells, Reproducibility of results, Sensitivity and Specificity, Time-Lapse Imaging}, issn = {1365-2818}, doi = {10.1111/j.1365-2818.2012.03678.x}, author = {Chalfoun, J and Kociolek, M and Dima, A and Halter, M and Cardone, Antonio and Peskin, A and Bajcsy, P and Brady, M.} } @article {19413, title = {Specific and Non-Specific Protein Association in Solution: Computation of Solvent Effects and Prediction of First-Encounter Modes for Efficient Configurational Bias Monte Carlo Simulations}, journal = {The Journal of Physical Chemistry B}, volume = {117}, year = {2013}, month = {May-10-2014}, pages = {12360 - 12374}, issn = {1520-6106}, doi = {10.1021/jp4050594}, url = {http://pubs.acs.org/doi/abs/10.1021/jp4050594}, author = {Cardone, Antonio and Pant, Harish and Hassan, Sergio A.} } @article {20064, title = {Understanding the impact of image quality on segmentation accuracy}, journal = {SPIE Newsroom}, year = {2013}, month = {2013}, author = {Li-Baboud, Ya-Shian and Cardone, Antonio and Chalfoun, Joe and Bajcsy, Peter and Elliott, John} } @article {20063, title = {Biases from model assumptions in texture sub-cellular image segmentation}, journal = {SPIE Newsroom}, volume = {13}, year = {2012}, author = {Cardone, Antonio and Amelot, Julien and Li-Baboud, Ya-Shian and Brady, Mary and Bajcsy, Peter} } @conference {19374, title = {Sub-cellular feature detection and automated extraction of collocalized actin and myosin regions}, booktitle = {the 2nd ACM SIGHIT symposiumProceedings of the 2nd ACM SIGHIT symposium on International health informatics - IHI {\textquoteright}12}, year = {2012}, pages = {399}, publisher = {ACM Press}, organization = {ACM Press}, address = {Miami, Florida, USANew York, New York, USA}, isbn = {9781450307819}, doi = {10.1145/211036310.1145/2110363.2110409}, author = {Martineau, Justin and Mokashi,Ronil and Chapman, David and Grasso, Michael and Brady,Mary and Yesha,Yelena and Yesha,Yaacov and Cardone, Antonio and Dima, Alden} } @article {19369, title = {Cell cycle dependent TN-C promoter activity determined by live cell imaging.}, journal = {Cytometry. Part A : the journal of the International Society for Analytical Cytology}, volume = {79}, year = {2011}, month = {2011 Mar}, pages = {192-202}, abstract = {The extracellular matrix protein tenascin-C plays a critical role in development, wound healing, and cancer progression, but how it is controlled and how it exerts its physiological responses remain unclear. By quantifying the behavior of live cells with phase contrast and fluorescence microscopy, the dynamic regulation of TN-C promoter activity is examined. We employ an NIH 3T3 cell line stably transfected with the TN-C promoter ligated to the gene sequence for destabilized green fluorescent protein (GFP). Fully automated image analysis routines, validated by comparison with data derived from manual segmentation and tracking of single cells, are used to quantify changes in the cellular GFP in hundreds of individual cells throughout their cell cycle during live cell imaging experiments lasting 62 h. We find that individual cells vary substantially in their expression patterns over the cell cycle, but that on average TN-C promoter activity increases during the last 40\% of the cell cycle. We also find that the increase in promoter activity is proportional to the activity earlier in the cell cycle. This work illustrates the application of live cell microscopy and automated image analysis of a promoter-driven GFP reporter cell line to identify subtle gene regulatory mechanisms that are difficult to uncover using population averaged measurements.}, keywords = {Animals, cell cycle, Gene Expression Regulation, Green Fluorescent Proteins, Image Processing, Computer-Assisted, Mice, Microscopy, Fluorescence, Microscopy, Phase-Contrast, NIH 3T3 Cells, Promoter Regions, Genetic, Tenascin}, issn = {1552-4930}, doi = {10.1002/cyto.a.21028}, author = {Halter, Michael and Sisan, Daniel R and Chalfoun, Joe and Stottrup, Benjamin L and Cardone, Antonio and Dima,Alden A. and Tona, Alessandro and Plant,Anne L. and Elliott, John T} } @article {12426, title = {Evaluation of the Interaction of Cyclin-Dependent Kinase 5 with Activator p25 and with p25-Derived Inhibitor CIP}, journal = {Journal of Computational Biology}, volume = {17}, year = {2010}, month = {2010///}, pages = {707 - 721}, author = {Cardone, Antonio and Albers,R.W. and Sriram,R.D. and Pant,H.C.} } @conference {12429, title = {Image classification of vascular smooth muscle cells}, booktitle = {Proceedings of the 1st ACM International Health Informatics Symposium}, series = {IHI {\textquoteright}10}, year = {2010}, month = {2010///}, pages = {484 - 486}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {cell biology, digital image processing, machine learning}, isbn = {978-1-4503-0030-8}, doi = {10.1145/1882992.1883068}, url = {http://doi.acm.org/10.1145/1882992.1883068}, author = {Grasso,Michael A. and Mokashi,Ronil and Dalvi,Darshana and Cardone, Antonio and Dima,Alden A. and Bhadriraju,Kiran and Plant,Anne L. and Brady,Mary and Yesha,Yaacov and Yesha,Yelena} } @article {19373, title = {Overlap-based cell tracker}, journal = {The Journal of Research of the National Institute of Standards and Technology}, volume = {115}, year = {2010}, month = {11/2010}, chapter = {477}, abstract = { order to facilitate the extraction of quantitative data from live cell image sets, automated image analysis methods are needed. This paper presents an introduction to the general principle of an overlap cell tracking software developed by the National Institute of Standards and Technology (NIST). This cell tracker has the ability to track cells across a set of time lapse images acquired at high rates based on the amount of overlap between cellular regions in consecutive frames. It is designed to be highly flexible, requires little user parameterization, and has a fast execution time. }, author = {Chalfoun, J and Cardone, Antonio and Dima, A.A. and Allen, D.P. and Halter, M.W.} } @article {19368, title = {Structural and dynamic determinants of ligand binding and regulation of cyclin-dependent kinase 5 by pathological activator p25 and inhibitory peptide CIP.}, journal = {Journal of molecular biology}, volume = {401}, year = {2010}, month = {2010 Aug 20}, pages = {478-92}, abstract = {The crystal structure of the cdk5/p25 complex has provided information on possible molecular mechanisms of the ligand binding, specificity, and regulation of the kinase. Comparative molecular dynamics simulations are reported here for physiological conditions. This study provides new insight on the mechanisms that modulate such processes, which may be exploited to control pathological activation by p25. The structural changes observed in the kinase are stabilized by a network of interactions involving highly conserved residues within the cyclin-dependent kinase (cdk) family. Collective motions of the proteins (cdk5, p25, and CIP) and their complexes are identified by principal component analysis, revealing two conformational states of the activation loop upon p25 complexation, which are absent in the uncomplexed kinase and not apparent from the crystal. Simulations of the uncomplexed inhibitor CIP show structural rearrangements and increased flexibility of the interfacial loop containing the critical residue E240, which becomes fully hydrated and available for interactions with one of several positively charged residues in the kinase. These changes provide a rationale for the observed high affinity and enhanced inhibitory action of CIP when compared to either p25 or the physiological activators of cdk5.}, keywords = {Crystallography, X-Ray, Cyclin-Dependent Kinase 5, Cyclin-Dependent Kinase Inhibitor Proteins, HUMANS, Ligands, molecular dynamics simulation, Nerve Tissue Proteins, Principal component analysis, Protein Binding, Protein Conformation}, issn = {1089-8638}, doi = {10.1016/j.jmb.2010.06.040}, author = {Cardone, Antonio and Hassan, S A and Albers,R.W. and Sriram,R.D. and Pant,H.C.} } @conference {12427, title = {Content-based search techniques for searching CAD databases}, booktitle = {CAD Conference}, year = {2006}, month = {2006///}, abstract = {The popularity of 3D CAD systems is resulting in large assembly and part databases being createdby product development organizations. Over the last few years several content-based techniques have emerged to search these databases. Ability to perform content-based searches on CAD databases is expected to help the designers and manufacturing engineers in many different ways. Representative examples include part-family formation, redesign suggestion generation, supplier selection, cost estimation, tooling design, machine selection, stock selection, and design reuse. This paper covers the following three topics. First, it presents an overview of different types of part search techniques. Second, it presents an overview of the different aspects of assembly search techniques. Finally, it identifies the open challenges in these areas and outlines future research directions. }, author = {Gupta, Satyandra K. and Cardone, Antonio and Deshmukh,A.} } @article {18856, title = {Machining feature-based similarity assessment algorithms for prismatic machined parts}, journal = {Computer-Aided Design}, volume = {38}, year = {2006}, month = {2006/09//}, pages = {954 - 972}, abstract = {This paper presents algorithms for identifying machined parts in a database that are similar to a given query part based on machining features. In this paper we only consider parts that are machined on 3-axis machining centers. We utilize reduced feature vectors consisting of machining feature access directions, feature types, feature volumes, feature dimensional tolerances and feature group cardinality as a basis for assessing shape similarity. We have defined a distance function between two sets of reduced feature vectors to assess the similarity between them from the machining effort point of view. To assess the similarity between the two parts, one set of reduced feature vectors is transformed in space using rigid body transformations with respect to the other set such that the distance between them is minimized. The distance between the two sets of aligned reduced feature vectors is used as a measure of similarity between the two parts. The existing machined parts are rank ordered based on the value of the distance with respect to the query part. The cost of previously machined parts that have a very small distance from the query part can be used as a basis for estimating the cost of machining the new part.}, keywords = {Feature vector alignment, Machining features, Similarity assessment}, isbn = {0010-4485}, doi = {10.1016/j.cad.2006.08.001}, url = {http://www.sciencedirect.com/science/article/pii/S0010448506001369}, author = {Cardone, Antonio and Gupta, Satyandra K. and Deshmukh,Abhijit and Karnik,Mukul} } @conference {19367, title = {Shape Similarity Assessment Based On Face Alignment Using Attributed Applied Vectors.}, booktitle = {CAD Conference}, year = {2006}, author = {Cardone, Antonio and Gupta, Satyandra K.} } @article {12431, title = {Using Iterative Strategies for Aligning Attributed Points in Space}, volume = {ISR-TR-2005-2}, year = {2005}, month = {2005///}, institution = {Institute for Systems Research, University of Maryland, College Park}, abstract = {Signatures based on shape features are expected to be useful for several similarity assessment applications. Such signatures can extract the relevant shape information needed for similarity assessment and ignore the shape information not needed for a particular application.

Since different feature-based models are created in different coordinate systems, in order to compute distance between two sets of features, one needs to include geometric transformations for aligning features. Optimal alignment is the alignment that results in the minimum distance between two sets of features. In general, features can be viewed as attributed points in space. Hence, we need to develop techniques for aligning attributed points in space.

This report introduces iterative strategies for optimally aligning attributed points in space. Iterative strategies presented in this report involve successively applying algorithms that perform alignment under restricted rigid body transformations (e.g., rotations only or translations only) to solve point alignment problems that require higher dimension transformations (e.g., combinations rotations and translations). Our preliminary experimental results show that the idea of using of iterative strategies to solve higher dimension attributed point alignment problems is promising and can be used to perform feature-based shape similarity assessment.}, keywords = {Technical Report}, url = {http://drum.lib.umd.edu//handle/1903/6467}, author = {Cardone, Antonio and Gupta, Satyandra K. and Mount, Dave} } @conference {12428, title = {Identifying similar parts for assisting cost estimation of prismatic machined parts}, booktitle = {ASME Design for Manufacturing Conference, Salt Lake City, Utah}, year = {2004}, month = {2004///}, author = {Cardone, Antonio and Gupta,S.K. and Karnik,M.} } @article {12430, title = {A Survey of Shape Similarity Assessment Algorithms for Product Design and Manufacturing Applications}, journal = {Journal of Computing and Information Science in EngineeringJ. Comput. Inf. Sci. Eng.}, volume = {3}, year = {2003}, month = {2003/06/00/}, pages = {109 - 118}, keywords = {CAD, computational geometry, production engineering computing, spatial reasoning}, doi = {10.1115/1.1577356}, url = {http://link.aip.org/link/?CIS/3/109/1}, author = {Cardone, Antonio and Gupta, Satyandra K. and Karnik,Mukul} }