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Institution

Jaypee Institute of Information Technology

EducationNoida, Uttar Pradesh, India
About: Jaypee Institute of Information Technology is a education organization based out in Noida, Uttar Pradesh, India. It is known for research contribution in the topics: Cluster analysis & Wireless sensor network. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.


Papers
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Journal ArticleDOI
TL;DR: A lightweight blockchain-based protocol called Directed Acyclic Graph-based V2G network (DV2G), which refers to any Distributed Ledger Technology (DLT) and not just the bitcoin chain of blocks, is proposed and is shown to be highly scalable and supports the micro-transactions required in V1G networks.
Abstract: The Vehicle-to-Grid (V2G) network is, where the battery-powered vehicles provide energy to the power grid, is highly emerging. A robust, scalable, and cost-optimal mechanism that can support the increasing number of transactions in a V2G network is required. Existing studies use traditional blockchain as to achieve this requirement. Blockchain-enabled V2G networks require a high computation power and are not suitable for micro-transactions due to the mining reward being higher than the transaction value itself. Moreover, the transaction throughput in the generic blockchain is too low to support the increasing number of frequent transactions in V2G networks. To address these challenges, in this paper, a lightweight blockchain-based protocol called Directed Acyclic Graph-based V2G network (DV2G) is proposed. Here blockchain refers to any Distributed Ledger Technology (DLT) and not just the bitcoin chain of blocks. A tangle data structure is used to record the transactions in the network in a secure and scalable manner. A game theory model is used to perform negotiation between the grid and vehicles at an optimized cost. The proposed model does not require the heavy computation associated to the addition of the transactions to the data structure and does not require any fees to post the transaction. The proposed model is shown to be highly scalable and supports the micro-transactions required in V2G networks.

151 citations

Journal ArticleDOI
TL;DR: Optimized lorazepam loaded PLGA nanoparticles (Lzp-PLGA-NPs) were radiolabelled with Technitium-99m for scintigraphy imaging and biodistribution studies in Sprague-Dawley rats to establish nose-to-brain pathway.
Abstract: The aim of the present study was to optimize lorazepam loaded PLGA nanoparticles (Lzp-PLGA-NPs) by investigating the effect of process variables on the response using Box-Behnken design. Effect of four independent factors, that is, polymer, surfactant, drug, and aqueous/organic ratio, was studied on two dependent responses, that is, z-average and % drug entrapment. Lzp-PLGA-NPs were successfully developed by nanoprecipitation method using PLGA as polymer, poloxamer as surfactant and acetone as organic phase. NPs were characterized for particle size, zeta potential, % drug entrapment, drug release behavior, TEM, and cell viability. Lzp-PLGA-NPs were characterized for drug polymer interaction using FTIR. The developed NPs showed nearly spherical shape with z-average 167–318 d·nm, PDI below 0.441, and −18.4 mV zeta potential with maximum % drug entrapment of 90.1%. In vitro drug release behavior followed Korsmeyer-Peppas model and showed initial burst release of with prolonged drug release of from optimized NPs up to 24 h. In vitro drug release data was found in agreement with ex vivo permeation data through sheep nasal mucosa. In vitro cell viability study on Vero cell line confirmed the safety of optimized NPs. Optimized Lzp-PLGA-NPs were radiolabelled with Technitium-99m for scintigraphy imaging and biodistribution studies in Sprague-Dawley rats to establish nose-to-brain pathway.

150 citations

Journal ArticleDOI
TL;DR: In this article, an improvement of magnetic properties in Co 2 + substituted Mg Zn nano-ferrites synthesized by co-precipitation route was reported, where a phase transition from superparamagnetic to ferrimagnetic behavior for x ǫ> 0.125 has been observed.

149 citations

Journal ArticleDOI
TL;DR: In this paper, a novel recycling process for obtaining silicon from the kerf loss powders is reported, and the obtained silicon after directional solidification was found to be of solar grade.

148 citations

Journal ArticleDOI
TL;DR: This review focuses on the applications of EGCG alone, and in combination with other compounds, for the treatment of various types of cancers, metabolic, neurodegenerative, and microbial diseases, and discusses its mechanism of action in cell line and animal modesl.
Abstract: Introduction: Green tea contains polyphenolic flavanoids such as epigallocatechin-3- gallate (EGCG), epicatechin-3-gallate (ECG), epigallocatechin (EGC) and epicatechin (EC). EGCG is the most abundant and active compound in green tea. Extensive research has shown that it has significant antioxidant, anti-carcinogenic, anti-microbial, and neuroprotective properties and has therapeutic potential against various human diseases.Areas covered: This review focuses on the applications of EGCG alone, and in combination with other compounds, for the treatment of various types of cancers, metabolic, neurodegenerative, and microbial diseases, and discusses its mechanism of action in cell line and animal modesl. Recent advances, which include the use of nanoencapsulated EGCG to enhance the drug delivery and reduce cell toxicity, have also been discussed along with the comprehensive analysis of the specific granted patents associated with EGCG.Expert opinion: Under the current scenario, the role of EGCG as a t...

146 citations


Authors

Showing all 2176 results

NameH-indexPapersCitations
Sanjay Gupta9990235039
Mohsen Guizani79111031282
José M. Merigó5536110658
Ashish Goel502059941
Avinash C. Pandey453017576
Krishan Kumar352424059
Yogendra Kumar Gupta351834571
Nidhi Gupta352664786
Anirban Pathak332143508
Amanpreet Kaur323675713
Navneet Sharma312193069
Garima Sharma31973348
Manoj Kumar301082660
Rahul Sharma301893298
Ghanshyam Singh292632957
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202321
202258
2021401
2020395
2019464
2018366