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Rahul Singh

Researcher at Indian Institute of Science

Publications -  370
Citations -  9332

Rahul Singh is an academic researcher from Indian Institute of Science. The author has contributed to research in topics: Chemistry & Medicine. The author has an hindex of 39, co-authored 285 publications receiving 7444 citations. Previous affiliations of Rahul Singh include Texas A&M University & University of British Columbia.

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The emerging role for bacteria in lignin degradation and bio-product formation

TL;DR: If biocatalytic routes for lignin breakdown could be developed, then lign in represents a potentially rich source of renewable aromatic chemicals.
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Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior

TL;DR: In this paper, the authors explored the relationship between social media marketing activities and consumers' behavior towards a brand and found that SMMEs have a significant positive effect on brand equity and on the two main dimensions of brand awareness and brand image.
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A review of tissue substitutes for ultrasound imaging.

TL;DR: This paper reviews ultrasound tissue-mimicking materials and phantom fabrication techniques that have been developed over the past four decades, and describes the benefits and disadvantages of the processes.
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Scheduling Policies for Minimizing Age of Information in Broadcast Wireless Networks

TL;DR: In this article, the authors consider a wireless broadcast network with a base station sending time-sensitive information to a number of clients through unreliable channels and formulate a discrete-time decision problem to find a transmission scheduling policy that minimizes the expected weighted sum AoI of the clients in the network.
Proceedings ArticleDOI

Social ties and their relevance to churn in mobile telecom networks

TL;DR: This paper examines the communication patterns of millions of mobile phone users, allowing it to study the underlying social network in a large-scale communication network and proposes a spreading activation-based technique that predicts potential churners by examining the current set of churners and their underlyingsocial network.