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..

Studies on the Dynamics of Powdery Mildews on Cucurbits in Haryana, India

Abstract: This study considered the occurrence of powdery mildew on cucurbits in Haryana and determined the identity of causal species of the disease in the state. Eleven cucurbits were found infected in one or the other locality in the study area of the state which comprised six districts located distantly. Bottle gourd (Lagenaria siceraria) was most severely affected crop. While Citrullus lanatus was least affected as comparision to other cucurbits. A wild cucurbit, Coccinia cordifolia, was also severely affected. Teleomorphs of the pathogen were found on L. siceraria and Cucumis melo. Utilizing anamorph and teleomorph characters, the species responsible for the disease in the state were identified as Podosphaera xanthii and Golovinomyces cichoracearum. Pathogenecity spectrum of disease in states is similarto several other states in India.

Latent max-margin metric learning for comparing video face tubes

Abstract: Comparing “face tubes” is a key component of modern systems for face biometrics based video analysis and annotation. We present a novel algorithm to learn a distance metric between such spatio-temporal face tubes in videos. The main novelty in the algorithm is based on incorporation of latent variables in a max-margin metric learning framework. The latent formulation allows us to model, and learn metrics to compare faces under different challenging variations in pose, expressions and lighting. We propose a novel dataset named TV Series Face Tubes (TSFT) for evaluating the task. The dataset is collected from 12 different episodes of 8 popular TV series and has 94 subjects with 569 manually annotated face tracks in total. We show quantitatively how incorporating latent variables in max-margin metric learning leads to improvement of current state-of-the-art metric learning methods for the two cases when the testing is done with subjects that were seen during training and when the test subjects were not seen at all during training. We also give results on a challenging benchmark dataset: YouTube faces, and place our algorithm in context w.r.t. existing methods.

Bulk Heterojunction Photovoltaics Using Broadly Absorbing Small Molecules Based on 2-Styryl-5-phenylazo-pyrrole

Abstract: Three new soluble small molecules (B, B6, and A) with a low band gap based on 2-styryl-5-phenylazo-pyrrole were synthesized. Molecules B and B6 contained pyrrole and N-hexylpyrrole, respectively, as the central unit, which was connected to N,N-dimethylphenyl-4-azo on one side of the pyrrole molecule. Molecule A contained N-hexylpyrrole as the central unit, which was connected to anthracenyl-9-azo on one side of the pyrrole molecule. The other side of the pyrrole molecule was connected to cyanovinylene 4-nitrophenyl for all molecules. The long-wavelength absorption maximum of the molecules was located at 601−637 nm, and their optical band gap was 1.62−1.67 eV. The photovoltaic properties have been investigated using blends of B, B6, or A with PCBM, and it was found that the device based on A:PCBM had a higher power conversion efficiency (PCE) (2.06%) than the devices based on B:PCBM (1.33%) and B6:PCBM (1.36%). This has been attributed to the higher hole mobility, the lower band gap of A relative to that o...

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.