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Institution

Motilal Nehru National Institute of Technology Allahabad

EducationAllahabad, Uttar Pradesh, India
About: Motilal Nehru National Institute of Technology Allahabad is a education organization based out in Allahabad, Uttar Pradesh, India. It is known for research contribution in the topics: Control theory & Electric power system. The organization has 2475 authors who have published 5067 publications receiving 61891 citations. The organization is also known as: NIT Allahabad & Motilal Nehru Regional Engineering College.


Papers
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Journal ArticleDOI
TL;DR: An Islanded DCMG is presented in which the PV system and the wind system connect with the DC bus through the interfacing devices (DC/DC boost and buck converters respectively) and their duty cycle is controlled by the P&O MPPT algorithm.

30 citations

Journal ArticleDOI
TL;DR: The robustness of the proposedDL-IMC scheme for load frequency control (LFC) issue of multi-area power systems is shown by introducing ± 50 % perturbations in the system parameters for different values of external load disturbances.

30 citations

Journal ArticleDOI
TL;DR: ROR2 is frequently epigenetically inactivated by promoter hypermethylation in the early stages of colorectal neoplasia and this may contribute to coloreCTal cancer progression by increasing cellular proliferation and migration.
Abstract: Colorectal cancer (CRC) is closely linked to Wnt signalling, with 94 % of cases exhibiting a Wnt related mutation. ROR2 is a receptor tyrosine kinase that is thought to repress β-catenin dependent Wnt signalling. Our study aims to determine if ROR2 is epigenetically silenced in CRC and determine if in vitro silencing of ROR2 potentiates Wnt signalling, and alters the proliferative, migratory or invasive potential of cells. ROR2 expression was examined in CRC cell lines and patient adenomas using qRT-PCR, while COBRA and bisulphite sequencing was used to analyse ROR2 promoter methylation. 258 patient primary tumour samples from publicly available databases were also examined for ROR2 expression and methylation. In addition, the functional effects of ROR2 modulation were investigated in HCT116 cells following ROR2 siRNA knockdown and in RKO and SW620 cells following ectopic ROR2 expression. Reduced ROR2 expression was found to correlate with ROR2 promoter hypermethylation in colorectal cancer cell lines, carcinomas and adenomas. ROR2 expression was downregulated in 76.7 % (23/30) of CRC cell lines with increasing ROR2 promoter hypermethylation correlating with progressively lower expression. Analysis of 239 primary tumour samples from a publicly available cohort also found a significant correlation between reduced ROR2 expression and increased promoter methylation. Methylation analysis of 88 adenomas and 47 normal mucosa samples found greater percentage of adenoma samples to be methylated. Additional analysis also revealed that adenoma samples with reduced ROR2 expression also possessed ROR2 promoter hypermethylation. ROR2 knockdown in the CRC cell line HCT116 significantly decreased expression of the β-catenin independent Wnt targets genes JNK and NFATC1, increased cellular proliferation and migration but decreased invasion. When ROR2 was ectopically expressed in RKO and SW620 cells, there was no significant change to either cellular proliferation or migration. ROR2 is frequently epigenetically inactivated by promoter hypermethylation in the early stages of colorectal neoplasia and this may contribute to colorectal cancer progression by increasing cellular proliferation and migration.

29 citations

Journal ArticleDOI
TL;DR: This study aimed to screen natural compounds as potential inhibitors of LasR, a transcription factor that controls QS in Pseudomonas aeruginosa, and selected six novel potential QS inhibiting compounds on the basis of binding energy.

29 citations

Journal ArticleDOI
TL;DR: In this article, the authors investigated the SARS CoV-2 virus particle transport and deposition to the terminal airways in a complex 17-generation lung model and showed that a higher percentage of the virus particles are trapped at the upper airways when sleeping and in a light activity condition.
Abstract: The recent outbreak of the SARS CoV-2 virus has had a significant effect on human respiratory health around the world. The contagious disease infected a large proportion of the world population, resulting in long-term health issues and an excessive mortality rate. The SARS CoV-2 virus can spread as small aerosols and enters the respiratory systems through the oral (nose or mouth) airway. The SARS CoV-2 particle transport to the mouth-throat and upper airways is analyzed by the available literature. Due to the tiny size, the virus can travel to the terminal airways of the respiratory system and form a severe health hazard. There is a gap in the understanding of the SARS CoV-2 particle transport to the terminal airways. The present study investigated the SARS CoV-2 virus particle transport and deposition to the terminal airways in a complex 17-generation lung model. This first-ever study demonstrates how far SARS CoV-2 particles can travel in the respiratory system. ANSYS Fluent solver was used to simulate the virus particle transport during sleep and light and heavy activity conditions. Numerical results demonstrate that a higher percentage of the virus particles are trapped at the upper airways when sleeping and in a light activity condition. More virus particles have lung contact in the right lung than the left lung. A comprehensive lobe specific deposition and deposition concentration study was performed. The results of this study provide a precise knowledge of the SARs CoV-2 particle transport to the lower branches and could help the lung health risk assessment system.

29 citations


Authors

Showing all 2547 results

NameH-indexPapersCitations
Santosh Kumar80119629391
Anoop Misra7038517301
Naresh Kumar66110620786
Munindar P. Singh6258020279
Arvind Agarwal5832512365
Mahendra Kumar542169170
Jay Singh513018655
Lalit Kumar4738111014
O.N. Srivastava4754810308
Avinash C. Pandey453017576
Sunil Gupta435188827
Rakesh Mishra415457385
Durgesh Kumar Tripathi371335937
Vandana Singh351904347
Prashant K. Sharma341743662
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202342
202284
2021728
2020587
2019532
2018423