Indian Institute of Technology Bombay

About: Indian Institute of Technology Bombay is a education organization based out in Mumbai, India. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 16756 authors who have published 33588 publications receiving 570559 citations.

Totarol inhibits bacterial cytokinesis by perturbing the assembly dynamics of FtsZ.

Abstract: Totarol, a diterpenoid phenol, has been shown to inhibit the proliferation of several pathogenic Gram-positive bacteria including Mycobacterium tuberculosis. In this study, totarol was found to inhibit the proliferation of Bacillus subtilis cells with a minimum inhibitory concentration of 2 μM. It did not detectably perturb the membrane structure of B. subtilis; it strongly induced the filamentation in B. subtilis cells, suggesting that it inhibits bacterial cytokinesis. Totarol (1.5 μM) reduced the frequency of the Z-ring occurrence per micrometer of the bacterial cell length but did not affect the nucleoid frequency, suggesting that it blocks cytokinesis by inhibiting the formation of the Z-ring. The assembly dynamics of FtsZ is thought to play an important role in the formation and functioning of the Z-ring, a machine that engineers cytokinesis in bacteria. Since totarol was shown to inhibit the proliferation of M. tuberculosis, we examined the effects of totarol on the assembly dynamics of M. tubercul...

Pileup subtraction for jet shapes.

Abstract: Jets in high energy hadronic collisions often contain the fingerprints of the particles that produced them. Those fingerprints, and thus the nature of the particles that produced the jets, can be read off with the help of quantities known as jet shapes. Jet shapes are, however, severely affected by pileup, the accumulation in the detector of the residues of the many simultaneous collisions taking place in the Large Hadron Collider (LHC). We introduce a method to correct for pileup effects in jet shapes. Relative to earlier, limited approaches, the key advance resides in its full generality, achieved through a numerical determination, for each jet, of a given shape's susceptibility to pileup. The method rescues the possibility of using jet shapes in the high pileup environment of current and future LHC running, as we show with examples of quark-gluon discrimination and top tagging.

Near N–S paleo-extension in the western Deccan region, India: Does it link strike-slip tectonics with India–Seychelles rifting?

Abstract: This is the first detailed report and analyses of deformation from the W part of the Deccan large igneous province (DLIP), Maharashtra, India. This deformation, related to the India–Seychelles rifting during Late Cretaceous–Early Paleocene, was studied, and the paleostress tensors were deduced. Near N–S trending shear zones, lineaments, and faults were already reported without significant detail. An E–W extension was envisaged by the previous workers to explain the India–Seychelles rift at ~64 Ma. The direction of extension, however, does not match with their N–S brittle shear zones and also those faults (sub-vertical, ~NE–SW/~NW–SE, and few ~N–S) we report and emphasize in this work. Slickenside-bearing fault planes, brittle shear zones, and extension fractures in meso-scale enabled us to estimate the paleostress tensors (directions and relative magnitudes). The field study was complemented by remote sensing lineament analyses to map dykes and shear zones. Dykes emplaced along pre-existing ~N–S to ~NE–SW/~NW–SE shears/fractures. This information was used to derive regional paleostress trends. A ~NW–SE/NE–SW minimum compressive stress in the oldest Kalsubai Subgroup and a ~N–S direction for the younger Lonavala, Wai, and Salsette Subgroups were deciphered. Thus, a ~NW/NE to ~N–S extension is put forward that refutes the popular view of E–W India–Seychelles extension. Paleostress analyses indicate that this is an oblique rifted margin. Field criteria suggest only ~NE–SW and ~NW–SE, with some ~N–S strike-slip faults/brittle shear zones. We refer this deformation zone as the "Western Deccan Strike-slip Zone" (WDSZ). The observed deformation was matched with offshore tectonics deciphered mainly from faults interpreted on seismic profiles and from magnetic seafloor spreading anomalies. These geophysical findings too indicate oblique rifting in this part of the W Indian passive margin. We argue that the Seychelles microcontinent separated from India only after much of the DLIP erupted. Further studies of magma-rich passive margins with respect to timing and architecture of deformation and emplacement of volcanics are required.

Elliptic flow of identified hadrons in Au+Au collisions at s NN =7.7-62.4 GeV

Abstract: Measurements of the elliptic flow, upsilon(2), of identified hadrons (pi(+/-), K-+/-, K-s(0), p, (p) over bar, phi, Lambda, (Lambda) over bar, Xi(-), (Xi) over bar (+), Omega(-), (Omega) over bar (+)) in Au + Au collisions at root s(NN) = 7.7, 11.5, 19.6, 27, 39, and 62.4 GeV are presented. The measurements were done at midrapidity using the time-projection chamber and the time-of-flight detectors of the Solenoidal Tracker at RHIC experiment during the beam-energy scan program at Relativistic Heavy Ion Collider. A significant difference in the upsilon(2) values for particles and the corresponding antiparticles was observed at all transverse momenta for the first time. The difference increases with decreasing center-of-mass energy, root s(NN) (or increasing baryon chemical potential, mu(B)), and is larger for the baryons as compared to the mesons. This implies that particles and antiparticles are no longer consistent with the universal number-of-constituent quark (NCQ) scaling of upsilon(2) that was observed at root s(NN) = 200 GeV. However, for the selected group of particles (p(+), K+, K-s(0), p, Lambda, Xi(-), Omega(-)) NCQ scaling at (m(T) - m(0))/n(q) > 0.4 GeV/c(2) is not violated within +/- 10%. The upsilon(2) values for f mesons at 7.7 and 11.5 GeV are approximately two standard deviations from the trend defined by the other hadrons at the highest measured p(T) values.

A scalable approximate model counter

Abstract: Propositional model counting (#SAT), i.e., counting the number of satisfying assignments of a propositional formula, is a problem of significant theoretical and practical interest. Due to the inherent complexity of the problem, approximate model counting, which counts the number of satisfying assignments to within given tolerance and confidence level, was proposed as a practical alternative to exact model counting. Yet, approximate model counting has been studied essentially only theoretically. The only reported implementation of approximate model counting, due to Karp and Luby, worked only for DNF formulas. A few existing tools for CNF formulas are bounding model counters; they can handle realistic problem sizes, but fall short of providing counts within given tolerance and confidence, and, thus, are not approximate model counters. We present here a novel algorithm, as well as a reference implementation, that is the first scalable approximate model counter for CNF formulas. The algorithm works by issuing a polynomial number of calls to a SAT solver. Our tool, ApproxMC, scales to formulas with tens of thousands of variables. Careful experimental comparisons show that ApproxMC reports, with high confidence, bounds that are close to the exact count, and also succeeds in reporting bounds with small tolerance and high confidence in cases that are too large for computing exact model counts. Authors would like to thank Henry Kautz and Ashish Sabhrawal for their valuable help in experiments, and Tracy Volz for valuable comments on the earlier drafts. Work supported in part by NSF grants CNS 1049862 and CCF-1139011, by NSF Expeditions in Computing project "ExCAPE: Expeditions in Computer Augmented Program Engineering," by BSF grant 9800096, by a gift from Intel, by a grant from Board of Research in Nuclear Sciences, India, and by the Shared University Grid at Rice funded by NSF under Grant EIA-0216467, and a partnership between Rice University, Sun Microsystems, and Sigma Solutions, Inc.