Institution
Tata Institute of Fundamental Research
Education•Mumbai, Maharashtra, India•
About: Tata Institute of Fundamental Research is a education organization based out in Mumbai, Maharashtra, India. It is known for research contribution in the topics: Magnetization & Large Hadron Collider. The organization has 7786 authors who have published 21742 publications receiving 622368 citations. The organization is also known as: TIFR.
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16 Aug 2010
TL;DR: In this article, the authors provided the first quantitative ultrastructural analysis and molecular characterization of the major endocytic pathway in fibroblasts, a pathway that provides rapid membrane turnover at the leading edge of migrating cells.
Abstract: Although the importance of clathrin- and caveolin-independent endocytic pathways has recently emerged, key aspects of these routes remain unknown. Using quantitative ultrastructural approaches, we show that clathrin-independent carriers (CLICs) account for approximately three times the volume internalized by the clathrin-mediated endocytic pathway, forming the major pathway involved in uptake of fluid and bulk membrane in fibroblasts. Electron tomographic analysis of the 3D morphology of the earliest carriers shows that they are multidomain organelles that form a complex sorting station as they mature. Proteomic analysis provides direct links between CLICs, cellular adhesion turnover, and migration. Consistent with this, CLIC-mediated endocytosis of key cargo proteins, CD44 and Thy-1, is polarized at the leading edge of migrating fibroblasts, while transient ablation of CLICs impairs their ability to migrate. These studies provide the first quantitative ultrastructural analysis and molecular characterization of the major endocytic pathway in fibroblasts, a pathway that provides rapid membrane turnover at the leading edge of migrating cells.
236 citations
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TL;DR: Results show that Mn incorporation competes very effectively with the donor-acceptor surface states for the energy transfer from the electron-hole pair excited across the band gap, and suggests an additional decay channel for the surface states via an energyTransfer from these states to the dopant levels.
Abstract: We have performed steady-state and time-resolved fluorescence studies on undoped and Mn-doped ZnS nanocrystals with approximately 16 A diameter. While there is no band-edge emission, the intensity of the steady-state blue fluorescence from ZnS surface states decreases upon Mn incorporation, which gives rise to an orange emission. These results show that Mn incorporation competes very effectively with the donor-acceptor surface states for the energy transfer from the electron-hole pair excited across the band gap. In both undoped and doped samples, the time-resolved fluorescence studies establish the presence of a distribution of decay lifetimes possibly due to a number of emission centers in the nanocrystals. A faster short-time decay of the blue emission in the Mn-doped samples compared to that in the undoped sample suggests an additional decay channel for the surface states via an energy transfer from these states to the dopant levels.
235 citations
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TL;DR: In this paper, the authors show that the minimum degree greedy algorithm achieves a performance ratio of (Δ+2)/3 for approximating independent sets in graphs with degree bounded by Δ.
Abstract: Theminimum-degree greedy algorithm, or Greedy for short, is a simple and well-studied method for finding independent sets in graphs. We show that it achieves a performance ratio of (Δ+2)/3 for approximating independent sets in graphs with degree bounded by Δ. The analysis yields a precise characterization of the size of the independent sets found by the algorithm as a function of the independence number, as well as a generalization of Turan's bound. We also analyze the algorithm when run in combination with a known preprocessing technique, and obtain an improved $$(2\bar d + 3)/5$$ performance ratio on graphs with average degree $$\bar d$$ , improving on the previous best $$(\bar d + 1)/2$$ of Hochbaum. Finally, we present an efficient parallel and distributed algorithm attaining the performance guarantees of Greedy.
235 citations
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University of Lisbon1, University of Cambridge2, Texas A&M University3, Florida State University4, Johns Hopkins University5, Argonne National Laboratory6, University of Wisconsin-Madison7, Lawrence Berkeley National Laboratory8, University of Vienna9, Stanford University10, Michigan State University11, Royal Holloway, University of London12, Moscow State University13, Fermilab14, Chonbuk National University15, CERN16, University of Freiburg17, Pontifical Catholic University of Chile18, University of Paris19, University of Delhi20, Austrian Academy of Sciences21, National Autonomous University of Mexico22, University of Würzburg23, University of Zurich24, Max Planck Society25, Indian Institute of Science26, Aristotle University of Thessaloniki27, University of Barcelona28, University of California, Davis29, University of Tokushima30, University of California, Santa Cruz31, University of Science and Technology of China32, Tsinghua University33, Uppsala University34, Tokyo Gakugei University35, Spanish National Research Council36, National Taiwan University37, University of Liverpool38, University of Warsaw39, University of Michigan40, Seoul National University41, Yonsei University42, University of Southampton43, University of Bonn44, University of Montpellier45, RWTH Aachen University46, Laboratoire d'Annecy-le-Vieux de physique des particules47, University of Pennsylvania48, Carleton University49, University of Florida50, University of Glasgow51, University of Tokyo52, University of Lyon53, Harish-Chandra Research Institute54, University of Colorado Boulder55, Kyoto University56, University of Minnesota57, University of Rochester58, Durham University59, Tata Institute of Fundamental Research60, Paul Scherrer Institute61, University of Hamburg62, Chung-Ang University63, University of Sheffield64, University of Chicago65, Tohoku University66, Peking University67
TL;DR: In this article, a supersymmetry Parameter Analysis SPA (SPA) scheme is proposed based on a consistent set of conventions and input parameters, which connect parameters in different schemes and relate the Lagrangian parameters to physical observables at LHC and high energy e(+)e(-) linear collider experiments, i.e., masses, mixings, decay widths and production cross sections for supersymmetric particles.
Abstract: High-precision analyses of supersymmetry parameters aim at reconstructing the fundamental supersymmetric theory and its breaking mechanism. A well defined theoretical framework is needed when higher-order corrections are included. We propose such a scheme, Supersymmetry Parameter Analysis SPA, based on a consistent set of conventions and input parameters. A repository for computer programs is provided which connect parameters in different schemes and relate the Lagrangian parameters to physical observables at LHC and high energy e(+)e(-) linear collider experiments, i.e., masses, mixings, decay widths and production cross sections for supersymmetric particles. In addition, programs for calculating high-precision low energy observables, the density of cold dark matter (CDM) in the universe as well as the cross sections for CDM search experiments are included. The SPA scheme still requires extended efforts on both the theoretical and experimental side before data can be evaluated in the future at the level of the desired precision. We take here an initial step of testing the SPA scheme by applying the techniques involved to a specific supersymmetry reference point.
234 citations
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TL;DR: In this paper, the number of light neutrino species is found to be Nv=3.30% CL with the constraints of the standard electroweak model, which rules out the possibility of a fourth type of LN at 98% CL.
234 citations
Authors
Showing all 7857 results
Name | H-index | Papers | Citations |
---|---|---|---|
Pulickel M. Ajayan | 176 | 1223 | 136241 |
Suvadeep Bose | 154 | 960 | 129071 |
Subir Sarkar | 149 | 1542 | 144614 |
Sw. Banerjee | 146 | 1906 | 124364 |
Dipanwita Dutta | 143 | 1651 | 103866 |
Ajit Kumar Mohanty | 141 | 1124 | 93062 |
Tariq Aziz | 138 | 1646 | 96586 |
Andrew Mehta | 137 | 1444 | 101810 |
Suchandra Dutta | 134 | 1265 | 87709 |
Kajari Mazumdar | 134 | 1295 | 94253 |
Bobby Samir Acharya | 133 | 1121 | 100545 |
Gobinda Majumder | 133 | 1523 | 87732 |
Eric Conte | 132 | 1206 | 84593 |
Prashant Shukla | 131 | 1341 | 85287 |
Alessandro Montanari | 131 | 1387 | 93071 |