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Manish Sharma

Bio: Manish Sharma is an academic researcher from University Institute of Engineering and Technology, Panjab University. The author has contributed to research in topics: Medicine & Population. The author has an hindex of 82, co-authored 1407 publications receiving 33361 citations. Previous affiliations of Manish Sharma include Bose Corporation & Indian Institute of Technology Bombay.


Papers
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Journal ArticleDOI
Joseph Adams1, Madan M. Aggarwal2, Zubayer Ahammed3, J. Amonett4  +363 moreInstitutions (46)
TL;DR: In this paper, the most important experimental results from the first three years of nucleus-nucleus collision studies at RHIC were reviewed, with emphasis on results of the STAR experiment.

2,750 citations

Journal ArticleDOI
TL;DR: MBSR is moderately effective in reducing stress, depression, anxiety and distress and in ameliorating the quality of life of healthy individuals; however, more research is warranted to identify the most effective elements of MBSR.

1,031 citations

Journal ArticleDOI
TL;DR: This paper conducted a comprehensive and systematic national assessment of COVID-19 vaccine hesitancy in a community-based sample of the American adult population, where a multi-item valid and reliable questionnaire was deployed online via mTurk and social media sites to recruit U.S adults from the general population.
Abstract: Given the results from early trials, COVID-19 vaccines will be available by 2021. However, little is known about what Americans think of getting immunized with a COVID-19 vaccine. Thus, the purpose of this study was to conduct a comprehensive and systematic national assessment of COVID-19 vaccine hesitancy in a community-based sample of the American adult population. A multi-item valid and reliable questionnaire was deployed online via mTurk and social media sites to recruit U.S. adults from the general population. A total of 1878 individuals participated in the study where the majority were: females (52%), Whites (74%), non-Hispanic (81%), married (56%), employed full time (68%), and with a bachelor's degree or higher (77%). The likelihood of getting a COVID-19 immunization in the study population was: very likely (52%), somewhat likely (27%), not likely (15%), definitely not (7%), with individuals who had lower education, income, or perceived threat of getting infected being more likely to report that they were not likely/definitely not going to get COVID-19 vaccine (i.e., vaccine hesitancy). In unadjusted group comparisons, compared to their counterparts, vaccine hesitancy was higher among African-Americans (34%), Hispanics (29%), those who had children at home (25%), rural dwellers (29%), people in the northeastern U.S. (25%), and those who identified as Republicans (29%). In multiple regression analyses, vaccine hesitancy was predicted significantly by sex, education, employment, income, having children at home, political affiliation, and the perceived threat of getting infected with COVID-19 in the next 1 year. Given the high prevalence of COVID-19 vaccine hesitancy, evidence-based communication, mass media strategies, and policy measures will have to be implemented across the U.S. to convert vaccines into vaccinations and mass immunization with special attention to the groups identified in this study.

648 citations

Journal ArticleDOI
23 Jan 2017-Nature
TL;DR: In this article, an alignment between the global angular momentum of a non-central collision and the spin of emitted particles is presented, revealing that the fluid produced in heavy ion collisions is the most vortical system so far observed.
Abstract: © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. The extreme energy densities generated by ultra-relativistic collisions between heavy atomic nuclei produce a state of matter that behaves surprisingly like a fluid, with exceptionally high temperature and low viscosity. Non-central collisions have angular momenta of the order of 1,000h, and the resulting fluid may have a strong vortical structure that must be understood to describe the fluid properly. The vortical structure is also of particular interest because the restoration of fundamental symmetries of quantum chromodynamics is expected to produce novel physical effects in the presence of strong vorticity. However, no experimental indications of fluid vorticity in heavy ion collisions have yet been found. Since vorticity represents a local rotational structure of the fluid, spin-orbit coupling can lead to preferential orientati on of particle spins along the direction of rotation. Here we present measurements of an alignment between the global angular momentum of a non-central collision and the spin of emitted particles (in this case the collision occurs between gold nuclei and produces Λ baryons), revealing that the fluid produced in heavy ion collisions is the most vortical system so far observed. (At high energies, this fluid is a quark-gluon plasma.) We find that Λ and hyperons show a positive polarization of the order of a few per cent, consistent with some hydrodynamic predictions. (A hyperon is a particle composed of three quarks, at least one of which is a strange quark; the remainder are up and down quarks, found in protons and neutrons.) A previous measurement that reported a null result, that is, zero polarization, at higher collision energies is seen to be consistent with the trend of our observations, though with larger statistical uncertainties. These data provide experimental access to the vortical structure of the nearly ideal liquid created in a heavy ion collision and should prove valuable in the development of hydrodynamic models that quantitatively connect observations to the theory of the strong force.

643 citations

Journal ArticleDOI
Khachatryan, Albert M. Sirunyan, Armen Tumasyan, Wolfgang Adam  +2118 moreInstitutions (3)
TL;DR: In this article, the performance and strategies used in electron reconstruction and selection at CERN LHC are presented based on data corresponding to an integrated luminosity of 19.7 inverse femtobarns, collected in proton-proton collisions at sqrt(s) = 8 TeV.
Abstract: The performance and strategies used in electron reconstruction and selection at CMS are presented based on data corresponding to an integrated luminosity of 19.7 inverse femtobarns, collected in proton-proton collisions at sqrt(s) = 8 TeV at the CERN LHC. The paper focuses on prompt isolated electrons with transverse momenta ranging from about 5 to a few 100 GeV. A detailed description is given of the algorithms used to cluster energy in the electromagnetic calorimeter and to reconstruct electron trajectories in the tracker. The electron momentum is estimated by combining the energy measurement in the calorimeter with the momentum measurement in the tracker. Benchmark selection criteria are presented, and their performances assessed using Z, Upsilon, and J/psi decays into electron-positron pairs. The spectra of the observables relevant to electron reconstruction and selection as well as their global efficiencies are well reproduced by Monte Carlo simulations. The momentum scale is calibrated with an uncertainty smaller than 0.3%. The momentum resolution for electrons produced in Z boson decays ranges from 1.7 to 4.5%, depending on electron pseudorapidity and energy loss through bremsstrahlung in the detector material.

633 citations


Cited by
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[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

01 Jan 2016
TL;DR: The using multivariate statistics is universally compatible with any devices to read, allowing you to get the most less latency time to download any of the authors' books like this one.
Abstract: Thank you for downloading using multivariate statistics. As you may know, people have look hundreds times for their favorite novels like this using multivariate statistics, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some harmful bugs inside their laptop. using multivariate statistics is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the using multivariate statistics is universally compatible with any devices to read.

14,604 citations

Journal ArticleDOI
30 Aug 2013-Science
TL;DR: Metal-organic frameworks are porous materials that have potential for applications such as gas storage and separation, as well as catalysis, and methods are being developed for making nanocrystals and supercrystals of MOFs for their incorporation into devices.
Abstract: Crystalline metal-organic frameworks (MOFs) are formed by reticular synthesis, which creates strong bonds between inorganic and organic units. Careful selection of MOF constituents can yield crystals of ultrahigh porosity and high thermal and chemical stability. These characteristics allow the interior of MOFs to be chemically altered for use in gas separation, gas storage, and catalysis, among other applications. The precision commonly exercised in their chemical modification and the ability to expand their metrics without changing the underlying topology have not been achieved with other solids. MOFs whose chemical composition and shape of building units can be multiply varied within a particular structure already exist and may lead to materials that offer a synergistic combination of properties.

10,934 citations

Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

Journal ArticleDOI
TL;DR: Findings from a meta-analysis of 213 school-based, universal social and emotional learning programs involving 270,034 kindergarten through high school students suggest that policy makers, educators, and the public can contribute to healthy development of children by supporting the incorporation of evidence-based SEL programming into standard educational practice.
Abstract: This article presents findings from a meta-analysis of 213 school-based, universal social and emotional learning (SEL) programs involving 270,034 kindergarten through high school students. Compared to controls, SEL participants demonstrated significantly improved social and emotional skills, attitudes, behavior, and academic performance that reflected an 11-percentile-point gain in achievement. School teaching staff successfully conducted SEL programs. The use of 4 recommended practices for developing skills and the presence of implementation problems moderated program outcomes. The findings add to the growing empirical evidence regarding the positive impact of SEL programs. Policy makers, educators, and the public can contribute to healthy development of children by supporting the incorporation of evidence-based SEL programming into standard educational practice.

5,678 citations