Institution
Indian Institute of Technology Madras
Facility•Chennai, Tamil Nadu, India•
About: Indian Institute of Technology Madras is a facility organization based out in Chennai, Tamil Nadu, India. It is known for research contribution in the topics: Catalysis & Heat transfer. The organization has 20118 authors who have published 36499 publications receiving 590447 citations.
Papers published on a yearly basis
Papers
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TL;DR: An inclusive search for the standard model Higgs boson produced with large transverse momentum (p_{T}) and decaying to a bottom quark-antiquark pair (bb[over ¯]) is performed using a data set of pp collisions collected with the CMS experiment at the LHC.
Abstract: An inclusive search for the standard model Higgs boson (H) produced with large transverse momentum (p_T) and decaying to a bottom quark-antiquark pair (bb) is performed using a data set of pp collisions at √s = 13 TeV collected with the CMS experiment at the LHC. The data sample corresponds to an integrated luminosity of
35.9 fb^(−1). A highly Lorentz-boosted Higgs boson decaying to bb is reconstructed as a single, large radius jet, and it is identified using jet substructure and dedicated b tagging techniques. The method is validated with Z → bb decays. The Z → bb process is observed for the first time in the single-jet topology with a local significance of 5.1 standard deviations (5.8 expected). For a Higgs boson mass of 125 GeV, an excess of events above the expected background is observed (expected) with a local significance of 1.5 (0.7) standard deviations. The measured cross section times branching fraction for production via gluon fusion of H → bb with reconstructed p_T > 450 GeV and in the pseudorapidity range −2.5 < η < 2.5 is 74 ± 48 (stat)^(+17)_(−10)(syst) fb, which is consistent within uncertainties with the standard model prediction.
106 citations
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TL;DR: The improved hybrid distribution static compensator (DSTATCOM) topology will have reduced weight, cost, rating, and size with improved efficiency and current compensation capability compared with the traditional topology.
Abstract: This paper proposes an improved hybrid distribution static compensator (DSTATCOM) topology to address some practical issues such as power rating, filter size, compensation performance, and power loss. An LCL filter has been used at the front end of a voltage source inverter (VSI), which provides better switching harmonics elimination while using much smaller value of an inductor as compared with the traditional L filter. A capacitor is used in series with an LCL filter to reduce the dc-link voltage of the DSTATCOM. This consequently reduces the power rating of the VSI. With reduced dc-link voltage, the voltage across the shunt capacitor of the LCL filter will be also less. It will reduce the power losses in the damping resistor as compared with the traditional LCL filter with passive damping. Therefore, the proposed DSTATCOM topology will have reduced weight, cost, rating, and size with improved efficiency and current compensation capability compared with the traditional topology. A systematic procedure to design the components of the passive filter has been presented. The effectiveness of the proposed DSTATCOM topology over traditional topologies is validated through both simulation and experimental studies.
106 citations
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TL;DR: Under suitable assumptions, the paper shows that the question of physical realizability is equivalent to a frequency domain (J,J) -unitary condition, which is important in controller synthesis since it is the transfer function matrix of the controller which determines the closed loop system behavior.
Abstract: A recently emerging approach to the feedback control of linear quantum systems involves the use of a controller which itself is a quantum linear system. This approach to quantum feedback control, referred to as coherent quantum feedback control, has the advantage that it does not destroy quantum information, is fast, and has the potential for efficient implementation. An important issue which arises both in the synthesis of linear coherent quantum controllers and in the modeling of linear quantum systems, is the issue of physical realizability. This issue relates to the property of whether a given set of linear quantum stochastic differential equations corresponds to a physical quantum system satisfying the laws of quantum mechanics. Under suitable assumptions, the paper shows that the question of physical realizability is equivalent to a frequency domain (J,J) -unitary condition. This is important in controller synthesis since it is the transfer function matrix of the controller which determines the closed loop system behavior.
106 citations
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TL;DR: The notion of surrounding hydrophobicity, which characterizes the hydrophobic behavior of residues in a protein environment, has been applied to the three‐dimensional structures of elongation factor‐Tu proteins and it is found that the thermophilic proteins are enriched with a hydrophilic environment.
Abstract: The stability of thermophilic proteins has been viewed from different perspectives and there is yet no unified principle to understand this stability. It would be valuable to reveal the most important interactions for designing thermostable proteins for such applications as industrial protein engineering. In this work, we have systematically analyzed the importance of various interactions by computing different parameters such as surrounding hydrophobicity, inter-residue interactions, ion-pairs and hydrogen bonds. The importance of each interaction has been determined by its predicted relative contribution in thermophiles versus the same contribution in mesophilic homologues based on a dataset of 373 protein families. We predict that hydrophobic environment is the major factor for the stability of thermophilic proteins and found that 80% of thermophilic proteins analyzed showed higher hydrophobicity than their mesophilic counterparts. Ion pairs, hydrogen bonds, and interaction energy are also important and favored in 68%, 50%, and 62% of thermophilic proteins, respectively. Interestingly, thermophilic proteins with decreased hydrophobic environments display a greater number of hydrogen bonds and/or ion pairs. The systematic elimination of mesophilic proteins based on surrounding hydrophobicity, interaction energy, and ion pairs/hydrogen bonds, led to correctly identifying 95% of the thermophilic proteins in our analyses. Our analysis was also applied to another, more refined set of 102 thermophilic-mesophilic pairs, which again identified hydrophobicity as a dominant property in 71% of the thermophilic proteins. Further, the notion of surrounding hydrophobicity, which characterizes the hydrophobic behavior of residues in a protein environment, has been applied to the three-dimensional structures of elongation factor-Tu proteins and we found that the thermophilic proteins are enriched with a hydrophobic environment. The results obtained in this work highlight the importance of hydrophobicity as the dominating characteristic in the stability of thermophilic proteins, and we anticipate this will be useful in our attempts to engineering thermostable proteins.
106 citations
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TL;DR: A fusion approach to determine inverse kinematics solutions of a six degree of freedom serial robot makes use of radial basis function neural network for prediction of incremental joint angles which in turn are transformed into absolute joint angles with the assistance of forward kinematic relations.
106 citations
Authors
Showing all 20385 results
Name | H-index | Papers | Citations |
---|---|---|---|
Pulickel M. Ajayan | 176 | 1223 | 136241 |
Xiaodong Wang | 135 | 1573 | 117552 |
C. N. R. Rao | 133 | 1646 | 86718 |
Archana Sharma | 126 | 1162 | 75902 |
Rama Chellappa | 120 | 1031 | 62865 |
R. Graham Cooks | 110 | 736 | 47662 |
Angel Rubio | 110 | 930 | 52731 |
Prafulla Kumar Behera | 109 | 1204 | 65248 |
J. Andrew McCammon | 106 | 669 | 55698 |
M. Santosh | 103 | 1344 | 49846 |
Sandeep Kumar | 94 | 1563 | 38652 |
Tom L. Blundell | 86 | 687 | 56613 |
R. Srikant | 84 | 432 | 26439 |
Zdenek P. Bazant | 82 | 301 | 20908 |
Raghavan Srinivasan | 80 | 959 | 37821 |