Institution
Shiv Nadar University
Education•Dadri, Uttar Pradesh, India•
About: Shiv Nadar University is a education organization based out in Dadri, Uttar Pradesh, India. It is known for research contribution in the topics: Population & Graphene. The organization has 1015 authors who have published 1924 publications receiving 18420 citations.
Papers published on a yearly basis
Papers
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TL;DR: Based on Fenton's reaction mechanism, the system proposed here will deactivate airborne microbes (bioaerosols) such as SARS-CoV-2 as discussed by the authors, which relies on using a highly porous clayglass open-cell structure as an easily reproducible and cheap material.
Abstract: An arduous need exists to discover rapid solutions to avoid the accelerated spread of coronavirus especially through the indoor environments like offices, hospitals, and airports. One such measure could be to disinfect the air, especially in indoor environments. The goal of this work is to propose a novel design of a wet scrubber-reactor to deactivate airborne microbes using circular economy principles. Based on Fenton's reaction mechanism, the system proposed here will deactivate airborne microbes (bioaerosols) such as SARS-CoV-2. The proposed design relies on using a highly porous clay-glass open-cell structure as an easily reproducible and cheap material. The principle behind this technique is an in-situ decomposition of hydrogen peroxide into highly reactive oxygen species and free radicals. The high porosity of a tailored ceramic structure provides a high contact area between atomized oxygen, free radicals and supplied polluted air. The design is shown to comply with the needs of achieving sustainable development goals.
9 citations
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TL;DR: These findings reveal that regulation of daughter cell separation in C. crescentus differs from that of E. coli and can serve as a model system to study bacterial cytokinesis and overexpression of AmiC in cells inhibited for cell division leads to lysis.
Abstract: Bacterial cell division is a complex process brought about by the coordinated action of multiple proteins. Separation of daughter cells during the final stages of division involves cleavage of new cell wall laid down at the division septum. In E. coli, this process is governed by the action of N-acetylmuramoyl-L-alanine amidases AmiA/B/C, which are regulated by their LytM activators EnvC and NlpD. While much is known about the regulation of septum cleavage in E. coli, the mechanism of daughter cell separation is not clear in Caulobacter crescentus, a dimorphic crescent-shaped bacterium. In this work, we characterized the role of AmiC, the only annotated amidase in C. crescentus. AmiC from C. crescentus is functional in E. coli and restores cell separation defects seen in E. coli amidase mutants, suggesting that AmiC has septum splitting activity. The medial localization of AmiC was independent of DipM, an LytM domain-containing endopeptidase. Our results indicate that enzymatic activity is essential for medial recruitment of AmiC. Overexpression of AmiC causes cell separation defects and formation of chains. Finally, overexpression of AmiC in cells inhibited for cell division leads to lysis. Collectively, our findings reveal that regulation of daughter cell separation in C. crescentus differs from that of E. coli and can serve as a model system to study bacterial cytokinesis.
9 citations
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TL;DR: In this paper, the effect of incorporation of hydrothermally prepared TiO2-Au nanocomposites in the photoanode of dye-sensitized solar cells (DSSCs), prepared from commercially availableTiO2 nanoparticles, has been investigated.
Abstract: In this report, the effect of incorporation of hydrothermally prepared TiO2–Au nanocomposites in the photoanode of dye-sensitized solar cells (DSSCs), prepared from commercially available TiO2 nanoparticles, has been investigated. Electrophoretic deposition technique has been utilized for nanocomposite-doped photoanode preparation. The formation of hydrothermally prepared TiO2–Au nanocomposites has been confirmed by the X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), UV–Vis spectroscopy. The HRTEM images establish that the particle size of Au nanoparticles dispersed in TiO2 matrix varies from 2 to 45 nm. TiO2–Au photoelectrode has been characterized by XRD, field emission scanning electron microscopy, Raman spectroscopy and photoluminescence spectroscopy in order to confirm the successful preparation of plasmonic photoanodes. Measurement of current–voltage characteristics of the plasmonic dye-sensitized solar cells under the solar simulator illumination (100 mW/cm2, AM 1.5) shows enormous enhancement of power conversion efficiency. The PCE of plasmonic DSSCs is 10.1%, which is 134% greater than the DSSCs with pristine TiO2 photoanode of the same thickness. Electro-impedance spectroscopy reveals that the back electron transfer from the conduction band of Au–TiO2 photoanode to either dye or electrolyte has been significantly suppressed in the DSSC with plasmonic photoelectrode.
9 citations
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TL;DR: This work focuses on link prediction for bipartite graphs that is based on two very important concepts—potential energy and mutual information, and presents Potential Energy-Mutual Information based similarity metric which helps in prediction of potential links.
Abstract: Link prediction in networks has applications in computer science, graph theory, biology, economics, etc. Link prediction is a very well studied problem. Out of all the different versions, link prediction for unipartite graphs has attracted most attention. In this work we focus on link prediction for bipartite graphs that is based on two very important concepts-potential energy and mutual information. In the three step approach; first the bipartite graph is converted into a unipartite graph with the help of a weighted projection, next the potential energy and mutual information between each node pair in the projected graph is computed. Finally, we present Potential Energy-Mutual Information based similarity metric which helps in prediction of potential links. To evaluate the performance of the proposed algorithm four similarity metrics, namely AUC, Precision, Prediction-power and Precision@K were calculated and compared with eleven baseline algorithms. The Experimental results show that the proposed method outperforms the baseline algorithms.
9 citations
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TL;DR: A role of glutathione (GSH) and other thiols are demonstrated in neutralizing the effect of peroxynitrite-mediated DNA damage through stable GSH-DNA adduct formation and supports the use of thiol supplements as a potential therapeutic strategy against severe Covid-19 cases and a Phase II clinical trial launched in early May 2020.
Abstract: Inflammation is an immune response to protect against various types of infections. When unchecked, acute inflammation can be life-threatening, as seen with the current coronavirus pandemic. Strong oxidants, such as peroxynitrite produced by immune cells, are major mediators of the inflammation-associated pathogenesis. Cellular thiols play important roles in mitigating inflammation-associated macromolecular damage including DNA. Herein, we have demonstrated a role of glutathione (GSH) and other thiols in neutralizing the effect of peroxynitrite-mediated DNA damage through stable GSH-DNA adduct formation. Our observation supports the use of thiol supplements as a potential therapeutic strategy against severe COVID-19 cases and a Phase II (NCT04374461) open-label clinical trial launched in early May 2020 by the Memorial Sloan Kettering Cancer Center.
9 citations
Authors
Showing all 1055 results
Name | H-index | Papers | Citations |
---|---|---|---|
Dinesh Mohan | 79 | 283 | 35775 |
Vijay Kumar Thakur | 74 | 375 | 17719 |
Robert A. Taylor | 62 | 572 | 15877 |
Himanshu Pathak | 56 | 259 | 11203 |
Gurmit Singh | 54 | 270 | 8565 |
Vijay Kumar | 51 | 773 | 10852 |
Dimitris G. Kaskaoutis | 43 | 135 | 5248 |
Ken Haenen | 39 | 288 | 6296 |
Vikas Dudeja | 39 | 143 | 4733 |
P. K. Giri | 38 | 158 | 4528 |
Swadesh M Mahajan | 38 | 255 | 5389 |
Rohini Garg | 37 | 88 | 4388 |
Rajendra Bhatia | 36 | 154 | 9275 |
Rakesh Ganguly | 35 | 240 | 4415 |
Sonal Singhal | 34 | 180 | 4174 |