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Institution

Shiv Nadar University

EducationDadri, 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
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Journal ArticleDOI
TL;DR: In this paper, the authors proposed a strategy of opening the economy that considers three things: Geography, Work From Home capability, and Centrality, and found that about 15% of workers can return to work following this.
Abstract: India is among the select countries which reacted quite early to the threat of COVID -19. It announced a nationwide lockdown at an early stage on 25th March 2020, which has now been extended till 3rd May 2020. This has helped keep the numbers of infections and death low in a densely populated country like India. By all indications, though, this is going to be a long fight. In all likelihood “back to normal” can only happen when a vaccine is discovered, produced and administered to a large population. According to epidemiologists, that may take up to two years. It is obvious that we cannot be in a lockdown that long. We have to find ways to let the economy function in a safe way. So far, the government’s strategy on opening up the economy hinges on primarily one aspect – geography. The strategy involves locating areas that have high number of infections and close those areas, while let the other areas operate. This will allow a very limited amount of economic activity. We look at the districts that have COVID – 19 infections and find it has a high correlation with nightlight density, which is a proxy for economic activity in the districts. This is corroborated by a report today which states that according to RBI 170 districts designated as Covid-19 hotspots account for 80% of the credit. Hence, using this as the only parameter is limiting. So, what can be done? We propose a strategy of opening the economy that considers three things: Geography, Work From Home capability, and Centrality. We start by looking at infection rates in a district on a rolling average basis, then look at two industry characteristics. The first is Work From Home (WFH) capability. We first look at occupations and find which of these can be performed from home. Then we decompose each industry into these occupations and figure out which of these industries can operate with limited on-site support. We find that about 15% of workers can return to work following this. Then finally we create a network of industries based on the inputs they use. Since all industries use output from other industries, it is important to let those industries operate that are more central in the network. We rank these industries according to centrality. We suggest that the industries which are above certain rank can be allowed to resume operations by maintain strict social distancing and hygiene using methods like alternate shifts etc. This will allow the economy to resume operations and limit the negative impact of COVID – 19.

11 citations

Journal ArticleDOI
17 Jun 2020-MethodsX
TL;DR: The merit of the following method over other synthesis techniques include its rapidity, ease of preparation, and no requirement of elaborate synthesis procedures and/or harmful chemicals.

11 citations

Journal ArticleDOI
TL;DR: The meta-analysis showed that although in half of the patients with newly observed hyperglycemia at baseline, it remained unresolved at a follow-up of 3 to 6 months, the total burden of hyperglyCEmia is slightly above 10%, 3 Months after initiating TB treatment.
Abstract: There is scarce evidence that tuberculosis (TB) can cause diabetes in those not previously known to be diabetic. Whilst the World Health Organization (WHO) recommends screening for Diabetes Mellitus (DM) at the onset of TB treatment, nevertheless, it remains to be elucidated which patients with TB-associated hyperglycemia are at higher risk for developing DM and stand to benefit from a more regular follow-up. This review aims to firstly quantify the reduction of newly detected hyperglycemia burden in TB patients who are on treatment over time; secondly, determine the burden of TB-associated hyperglycemia after follow-up, and thirdly, synthesize literature on risk factors for unresolved TB-associated hyperglycemia in previously undiagnosed individuals. We searched PUBMED, EMBASE, SCOPUS, and Global Health for articles on TB-associated hyperglycemia up to September 30th, 2019. Search terms included Tuberculosis and hyperglycemia/DM, and insulin resistance. We appraised studies, extracted data, and conducted a meta-analysis to assess the change of the burden of hyperglycemia in prospective studies. The review is registered in the PROSPERO database (CRD42019118173). Eleven studies were included in the meta-analysis yielding a total of 677 (27,3%) of patients with newly detected hyperglycemia at baseline. The mean quality score of eligible studies using the Newcastle-Ottawa Quality Assessment Scale was 7.1 out of 9 (range 6-9). The pooled unresolved new cases of hyperglycemia at the end of follow up was 50% (95% CI: 36–64%) and the total pooled burden of hyperglycemia at 3–6 months of follow up was 11% (95% CI: 7–16%), with both estimates displaying a high heterogeneity, which remained significant after performing a sub-analysis by DM diagnostic method and 3 months of follow up. As only 2 studies explored risk factors for unresolved hyperglycemia, no meta-analysis was performed on risk factors. Our meta-analysis showed that although in half of the patients with newly observed hyperglycemia at baseline, it remained unresolved at a follow-up of 3 to 6 months, the total burden of hyperglycemia is slightly above 10%, 3 months after initiating TB treatment. Studies are warranted to assess whether risk factors including HIV positivity, smoking, and extensive pulmonary TB disease put patients at higher risk for DM.

11 citations

Book ChapterDOI
01 Jan 2016
TL;DR: In this article, a comparison of univariate and multivariate methods for spatial interpolation of rainfall in complex terrain of Indian Himalayas in Uttarakhand region is presented, where the role of topography in explaining the spatial variability of rainfall, elevation and slope calculated from DEM are incorporated as covariables in multivariate interpolation methods.
Abstract: Reliable estimation of rainfall distribution in mountainous regions poses a great challenge not only due to complex relationships between irregular topography and precipitation, but also due to non-availability of abundant rainfall measurement points. This study presents a comparison of univariate and multivariate methods for spatial interpolation of rainfall in complex terrain of Indian Himalayas in Uttarakhand region. To understand the role of topography in explaining the spatial variability of rainfall, elevation and slope calculated from DEM are incorporated as covariables in multivariate interpolation methods. Further, the study area is divided into three different regions based on variation in the elevation of topography and the performance of different spatial interpolation methods is analyzed for subdivided regions. The normal annual rainfall data of 80 rain gauge stations spread over 53,484 km2 is used to generate rainfall map using different interpolation methods. Cross validation is used to compare the prediction performances of the three multivariate geostatistical interpolation algorithms: simple kriging with varying local means (SKlm), ordinary cokriging (OCK), regression kriging (RK) and two univariate techniques: inverse distance weighted (IDW) and ordinary kriging (OK). The inclusion of elevation or slope as auxiliary variables improves the prediction of rainfall in mountainous region. SKlm performs better than OCK in all the cases. Residual kriging outperforms SKlm in Shivalik and Lesser Himalayas region where the correlation between rainfall and elevation is high (rshivalik = 0.79, rlesserhimalayas = 0.5). Also, OCK proves to be a better choice than OK only when the correlation between the rainfall and secondary variable (elevation or slope in this case) is good. When the data of Shivalik region (r=0.79) is considered, the RMSE of OCK is 363 and that of OK is 368. The prediction using OK and OCK yields similar result when the correlation between rainfall and elevation is moderate (r < 0.4). For all the cases, residual kriging outperforms OCK.

11 citations

Journal ArticleDOI
TL;DR: In this paper, the relativistic drive peaks near the innermost stable circular orbit (isco), whereas the baroclinic drive dominates at larger distances, leading to a "stronger" generation of vorticity than its Schwarzschild counterpart.
Abstract: Vorticity generation in accretion disks around Schwarzschild and Kerr black holes is investigated in the context of magnetofluid dynamics derived for both General Relativity (GR) and modified gravity formulations. In both cases, the Kerr geometry leads to a ``stronger'' generation of vorticity than its Schwarzschild counterpart. Of the two principal sources, the relativistic drive peaks near the innermost stable circular orbit (isco), whereas the baroclinic drive dominates at larger distances. Consequences of this new relativistic vorticity source are discussed in several astrophysical settings.

11 citations


Authors

Showing all 1055 results

NameH-indexPapersCitations
Dinesh Mohan7928335775
Vijay Kumar Thakur7437517719
Robert A. Taylor6257215877
Himanshu Pathak5625911203
Gurmit Singh542708565
Vijay Kumar5177310852
Dimitris G. Kaskaoutis431355248
Ken Haenen392886296
Vikas Dudeja391434733
P. K. Giri381584528
Swadesh M Mahajan382555389
Rohini Garg37884388
Rajendra Bhatia361549275
Rakesh Ganguly352404415
Sonal Singhal341804174
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20239
202256
2021356
2020322
2019227
2018176