Gaurav Sharma

Bio: Gaurav Sharma is an academic researcher from Shenzhen University. The author has contributed to research in topics: Medicine & Photocatalysis. The author has an hindex of 82, co-authored 1244 publications receiving 31482 citations. Previous affiliations of Gaurav Sharma include Northeastern University & D. E. Shaw & Co..

Swift: Scalable weighted iterative sampling for flow cytometry clustering

Abstract: Flow cytometry (FC) is a powerful technology for rapid multivariate analysis and functional discrimination of cells. Current FC platforms generate large, high-dimensional datasets which pose a significant challenge for traditional manual bivariate analysis. Automated multivariate clustering, though highly desirable, is also stymied by the critical requirement of identifying rare populations that form rather small clusters, in addition to the computational challenges posed by the large size and dimensionality of the datasets. In this paper, we address these twin challenges by developing a two-stage scalable multivariate parametric clustering algorithm. In the first stage, we model the data as a mixture of Gaussians and use an iterative weighted sampling technique to estimate the mixture components successively in order of decreasing size. In the second stage, we apply a graph-based hierarchical merging technique to combine Gaussian components with significant overlaps into the final number of desired clusters. The resulting algorithm offers a reduction in complexity over conventional mixture modeling while simultaneously allowing for better detection of small populations. We demonstrate the effectiveness of our method both on simulated data and actual flow cytometry datasets.

Fusing structure from motion and lidar for dense accurate depth map estimation

Abstract: We present a novel framework for precisely estimating dense depth maps by combining 3D lidar scans with a set of uncalibrated camera RGB color images for the same scene. Rough estimates for 3D structure obtained using structure from motion (SfM) on the uncalibrated images are first co-registered with the lidar scan and then a precise alignment between the datasets is estimated by identifying correspondences between the captured images and reprojected images for individual cameras from the 3D lidar point clouds. The precise alignment is used to update both the camera geometry parameters for the images and the individual camera radial distortion estimates, thereby providing a 3D-to-2D transformation that accurately maps the 3D lidar scan onto the 2D image planes. The 3D to 2D map is then utilized to estimate a dense depth map for each image. Experimental results on two datasets that include independently acquired high-resolution color images and 3D point cloud datasets indicate the utility of the framework. The proposed approach offers significant improvements on results obtained with SfM alone.

In - Vivo Assessment of Enhanced Bioavailability of Metronidazole with Piperine in Rabbits

Abstract: Piperine was established as being able to increase the bioavailability of a large number of drugs. So an attempt has been taken to study changes in bioavailability of metronidazole in presence of piperine in rabbits. Male New Zealand white rabbits (2.0-2.5 kg body weight) used for pharmacokinetic and bioavailability study. Three groups of rabbits were formed from which one group was considered as control and received only vehicle (distilled water) orally. Remaining two groups were treated with metronidazole and combination of metronidazole and piperine respectively. About one ml of blood sample was collected at the different time intervals and analyzed spectrophotometrically by HPLC. A Cmax value of 3,805.89 ± 233.8 ng/ml was obtained with metronidazole alone (20 mg/ kg) and 6,007.07 ± 348.8 ng/ml was obtained with a combination of metronidazole (20 mg/kg) and piperine (10 mg/kg). This represents an increase of 57% in peak plasma levels of metronidazole. Reduction in total clearance from 0.06 ± 0.02 to 0.04 ± 0.02 ml/h, and a volume of distribution from 2.69 ± 0.23 to 1.48 ± 0.65 L resulted in a net increase of 88.53% in AUC (45,073.75 ± 713.7 to 84,980.98 ± 345.6 ng * h/ml). So we can conclude that bioavailability of metronidazole was significantly enhance in the

Classification of Symmetric Key Management Schemes for Wireless Sensor Networks

Abstract: WSN is the collection of thousands of tiny sensor nodes, which have the capability of sensing, computing and transmitting the information in the network. Due to the low circuit design, it has some resource constraints but efficient to carry the information through wireless communication. But the exchange of information in a secure manner is critical in WSN. There are many techniques developed in recent years for the security purposes, one of the area is the key management. Key management is the challenging issue in sensor networks. In this paper we present the key management techniques for wireless sensor networks and classification has been presented based on the encryption techniques.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.